Pollutant Emissions Research Articles

Air pollution impacts of amine scrubbing for CO2 capture

The current political discussion in the United States around carbon capture and storage includes statements that suggest a need for a technical review to clarify the expected air pollution impacts of amine scrubbing. The Center for International Law and 50 other organizations published an open letter claiming that “CCS is not consistent with the principles of environmental justice… CCS makes dirty energy even more dangerous for frontline communities. Facilities equipped with carbon capture technology have to burn more fossil fuel to get the same energy output, resulting in increased emissions of toxic and hazardous pollutants, like fine particulates (PM2.5).”This paper reviews air pollutants produced by the use of amine scrubbing on coal- and gas-fired power plants in the U.S. and the process features and mitigation strategies that will minimize their impact on air quality. Even with atmospheric reactions, emissions of amine, nitrosamine, and other air toxics are likely to have insignificant environmental and health impacts. Stacks will disperse emissions with a dilution factor greater than 8000. Water wash with or without acid will reduce emissions of amine and nitrosamine that is produced from atmospheric reactions. Nitrosamine emissions will be managed with selective catalytic reduction (SCR) to reduce the NO/NO2 and/or selection of primary or non-volatile amines. With coal-fired power plants, amine aerosols, Hg, SO3, and fine particulate emissions will probably be managed by a fabric filter with alkali addition. Carbon capture by amine scrubbing will reduce significantly the effect of the power plant emissions on ambient levels of PM2.5. With coal-fired power plants, the application of amine scrubbing will significantly reduce SO2 emissions. NOx emissions will usually be minimized by selective catalytic reduction (SCR) in both gas- and coal-fired plants. Ammonia emissions will be minimized by managing amine oxidation, and if necessary, by adding an acid wash or other controls.

Optimal economic environmental power dispatch by using artificial bee colony algorithm

<span>Today, most power plants worldwide use fossil fuels such as natural gas, coal, and oil as the primary resource for energy reproduction primarily. The new term for economic environmental power dispatch (EEPD) problems is on the minimum total cost of the generator and fossil fuel emissions to address atmosphere pollution. Thus, the significant objective functions are identified to minimize the cost of generation, most minor emission pollutants, and lowest system losses individually. As an alternative, an Artificial Bee Colony (ABC) swarming algorithm is applied to solve the EEPD problem separately in the power systems on both standard IEEE 26 bus system and IEEE 57 bus system using a MATLAB programming environment. The performance of the introduced algorithm is measured based on simple mathematical analysis such as a simple deviation and its percentage from the obtained results. From the mathematical measurement, the ABC algorithm showed an improvement on each identified single objective function as compared with the gradient approach of using the Newton Raphson method in a short computational time.</span>

A New Perspective on Estimation of Gas Flaring Volume From Space: OLI/TIRS, VIIRS, and TROPOMI

AbstractGas flaring (GF) has the negative impact on the environment, climate, and human health. So, regular monitoring of flares and quantification of their volume is necessary. Iran has many natural oil/gas processing plants and petrochemical companies which are concentrated in the southern region. Pars Special Economic Energy Zone (PSEEZ) is an industry part with different kinds of active flares, thus a significant potential source of environmental impacts due to gas flaring. Remotely sensed data are used in gas‐flaring detection, volume estimation, and pollution emission. In this study, we applied day/nighttime radiation and air pollutant data to estimate gas flaring volumes. We developed artificial neural network models (ANN) for finding the relationship between the field measurement of GF volume as the dependent variable and shortwave infrared and thermal infrared bands of Landsat 8, M10 band of Visible Infrared Imaging Radiometer Suite, and air pollutant (NO2, CO, O3, and SO2) of TROPOMI as independent variables. Results showed that R2 values were 0.73 for the ANN model from 2018 to 2019. The sensitivity analysis demonstrated that the thermal infrared bands of B10 and B11 of Landsat 8 had the most important role in the estimation of gas flaring volume. In contrast, the SWIR bands of Landsat 8 and all TROPOMI products were insignificant. The findings of this research help to shed light on the use of remotely sensed data in estimating the volume of gas flaring at the regional/global scale by integration of the ANN model.

Analysis of the Hybrid Power-Heating System in a Single-Family Building, along with Ecological Aspects of the Operation

This study evaluates a hybrid heating system in a single-family building in northeastern Poland, which has a temperate continental climate. The analysis covers two heating seasons in 2021/2022 and 2022/2023. The hybrid heating system includes an air heat pump HPA–08 CS Plus with a heating power of 8.2 kW (AHP), a condensing gas boiler VC146/5–5 with a power of 14 kW (GB–Condens.), and a solid fuel boiler with a power of 11 kW for central heating. Additionally, hot water is heated by a Basic 270 (DHW’s AHP) air–water heat pump with a power of 2 kW, utilizing a tank with a capacity of 270 dm3 equipped with two heating coils. The building’s average electricity consumption is around 5400 kWh/year. A 4.96 kWp photovoltaic installation is installed on the building’s roof at a 40° angle towards the south to supplement the hybrid system. The study aims to assess whether the PV installation can adequately cover the energy needs of the hybrid heat source for heating and hot water. Furthermore, the study calculates the emission of pollutants (CO2, SOx, NOx, CO, and PM10) into the atmosphere. The total annual electricity production from PV installations was 5444.9 kWh in 2021/2022 and 5684.8 kWh in 2022/2023. The excess electricity was stored in the PGE power grid as per the Prosumer settlement rules. The installed PV installation is sufficient to power the following devices annually: AHP, DHW’s AHP, and GB–Condens. However, the daily electricity production from the PV installation is not enough to cover the energy needs of the heat pump for heating during the cold months in Poland (I–III, XI–XII). It can meet the power needs of a PC all year round and can also be stored during the summer months, for example, in energy warehouses or by directly storing it in the PGE power grid. The use of the PV installation resulted in an average reduction in pollutant emissions into the atmosphere: CO2—94.1%, SOx—91.8%, NOx—95.6%, CO—9.7%, and PM10—32.1%.

Clearing the smog ceiling: The impact of women’s political empowerment on air quality in European regions

This study explores the impact of female political empowerment on air quality outcomes. Women’s stronger environmental concerns and pro-environmental behaviors may lead to better air quality as they progressively break the glass ceiling in politics. To test this hypothesis, we employ a novel data set on regional air pollutant emissions and women’s political empowerment for a sample of 230 European regions of 27 EU countries. We apply instrumental variables and partial identification methods to ensure that our results are not influenced by confounding variables. We find that female political empowerment is consistently associated with improved air quality.

Multi-Criteria Optimization of a Laboratory Top-Lit Updraft Gasifier in Order to Reduce Greenhouse Gases and Particulate Matter Emissions

Air pollution from combustion processes is harming human health and the environment. To mitigate this, one needs to adopt cleaner energy production methods, in particular, to optimize combustion systems in order to minimize pollutants and increase efficiency. Flue gas analysis and particulate matter (PM) monitoring, starting from the prototype phase, is crucial to minimize and regulate pollutant emissions. This article analyses the emissions of pollutants and particulate matter from a combustion test gasifier working on the Top-Lit Updraft (TLUD) principle in order to optimize functionality and reduce exhaust emissions. Three experiments were performed in which the primary (gasification) air flow rate (GA) was kept constant at 25 L/min, and the secondary (combustion) air flow rate (CA) was adjusted to obtain a CA/GA ratio of 2 (50 L/min), 3 (75 L/min), and 4 (100 L/min) respectively. Based on a multi-criterial analysis, the optimal CA/GA ratio for TLUD combustion is 3, offering a well-rounded performance in output temperatures, PM and greenhouse gases (GHG) emissions, and efficiency, while the CA/GA ratio of 4 has good PM and GHG emissions performance but lower efficiency, and the CA/GA ratio of 2 is the least favorable due to its poor performance in output temperatures, PM and GHG emissions.

Experimental Study of Pollutant Emissions from Biomass Combustion and Modeling of PM Transportation

Experimental Study of Pollutant Emissions from Biomass Combustion and Modeling of PM Transportation

Impact of Air Quality on Respiratory Health in Children in Mexico

Purpose: The aim of the study was to analyze the impact of air quality on respiratory health in children in Mexico. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: High air pollution levels in Mexico, largely from traffic and industry, worsen respiratory health in children. This includes higher rates of asthma, respiratory infections, and decreased lung function. Urban areas with limited healthcare access are hit hardest. Urgent action is needed, including stricter regulations and public health initiatives, to protect Mexican children's well-being. Unique Contribution to Theory, Practice and Policy: Environmental determinism theory, bronfenbrenner’s ecological systems theory & health belief model (HBM) may be used to anchor future studies on analyze the impact of air quality on respiratory health in children in Mexico. Encourage pediatricians and healthcare providers to routinely discuss air quality issues during visits and provide guidance on minimizing exposure, especially in areas with known poor air quality. Policy initiatives should aim to reduce the emission of key pollutants identified in the research as harmful to children's respiratory health.

Influence of Air Quality on Respiratory Health in Urban Areas in Japan

Purpose: The aim of the study was to analyze the influence of air quality on respiratory health in urban areas in Japan. Methodology: This study adopted a desk methodology. A desk study research design is commonly known as secondary data collection. This is basically collecting data from existing resources preferably because of its low cost advantage as compared to a field research. Our current study looked into already published studies and reports as the data was easily accessed through online journals and libraries. Findings: Research in Japan indicates a clear link between urban air quality and respiratory health, with pollutants like PM2.5 and nitrogen dioxide posing significant risks. High pollution levels, stemming from factors like vehicular emissions and industrial activities, are particularly detrimental in densely populated areas. Vulnerable groups, such as children and the elderly, are especially affected, experiencing worsened symptoms and reduced lung function. Urgent implementation of effective air quality management measures is crucial to protect public health in Japanese cities. Unique Contribution to Theory, Practice and Policy: Environmental justice theory, exposure-response theory & place-based theory may be used to anchor future studies on analyze the influence of air quality on respiratory health in urban areas in Japan. Implement community-based interventions that target vulnerable populations, such as children, the elderly, and individuals with pre-existing respiratory conditions, in collaboration with local stakeholders and healthcare providers. Advocate for stricter air quality standards and regulations at the local, national, and international levels to reduce emissions of pollutants from industrial sources, transportation, and residential activities.

A metaheuristic approach to compare different combined economic emission dispatch methods involving load shifting policy

AbstractDistributed generators (DGs), which can be traditional fossil fuel generators or renewable energy sources (RES), must be appropriately planned in order to reduce a power network’s overall generating cost. Renewable energy sources (RES) should be prioritized because they provide a clean and sustainable energy supply and are abundant in nature. Demand side management (DSM) optimizes the scheduling of flexible loads to reduce peak demand and improve the load factor, while keeping daily demand unchanged. The test system in this research employs a dependable and effective hybrid optimization tool to plan the DGs of a dynamic system in a way that matches low active power production costs with low pollutant emissions. The fitness functions used in the test system were non-linear due to the presence of the valve point effect (VPE). The costs and emissions were evaluated for various fitness functions which included involvement of wind, DSM, and different types of combined economic emission dispatch (CEED) methods. The test system’s peak demand was cut by 12% and the load factor was raised from 0.7528 to 0.85 when DSM technique was used. The generation cost has been reduced from $1,014,996 to $1,012,182 using CSAJAYA algorithm which was further reduced to $1,007,441 after incorporating DSM. Likewise, the CEEDppf was also observed to be reduced to $1,231,435 and $1,216,885 with and without DSM compared to $1,232,001 from reported literature. Numerical results show that both the cost and emission were reduced significantly using the proposed CSAJAYA compared to a long-sighted list of algorithms published in literature. Graphical Abstract

Quantifying air quality co-benefits to industrial decarbonization: the local Air Emissions Tracking Atlas

IntroductionMany decarbonization technologies have the added co-benefit of reducing short-lived climate pollutants, such as particulate matter (PM), nitrogen oxides (NOx), and sulfur dioxide (SO2), creating a unique opportunity for identifying strategies that promote both climate change solutions and opportunities for air quality improvement. However, stakeholders and decision-makers may struggle to quantify how these co-benefits will impact public health for the communities most affected by industrial air pollution.MethodsTo address this problem, the LOCal Air Emissions Tracking Atlas (LOCAETA) fills a data availability and analysis gap by providing estimated air quality benefits from industrial decarbonization options, such as carbon capture and storage (CCS). These co-benefits are calculated using an algorithm that connects disparate datasets that separately report greenhouse gas emissions and other pollutants at U.S. industrial facilities.ResultsVersion 1.0 of LOCAETA displays the estimated primary PM2.5 emission reduction co-benefits from additional pretreatment equipment for CCS on industrial and power facilities across the state of Louisiana, as well as the potential for VOC and NH3 generation. The emission reductions are presented in the tool alongside facility pollutant emissions information and relevant air quality, environmental, demographic, and public health datasets, such as air toxics cancer risk, satellite and in situ pollutant measurements, and population vulnerability metrics.DiscussionLOCAETA enables regulators, policymakers, environmental justice communities, and industrial and commercial users to compare and contrast quantifiable public health benefits due to air quality impacts from various climate change mitigation strategies using a free and publicly-available tool. Additional pollutant reductions can be calculated using the same methodology and will be available in future versions of the tool.

Experimental and DFT Studies of Influence of Flue Gas Components on the Interaction between CaO and As during Sludge Combustion

The problem of As pollution emission from sludge during combustion has received widespread attention. The impact of flue gas components on the interaction with CaO and As during sludge combustion was analyzed using a series of experimental characterization methods. The strength of the activity of As2O3 on the CaO(001) surface as well as on the CO2/SO2/H2O+CaO(001) surface with different O adsorption sites was revealed by combining with Density Functional Theory (DFT). According to the results, CO2 in the flue gas reacted with CaO in a reversible carbonation reaction, which optimized the pore structure of the solid phase products and promoted the capture of As by CaO. SO2 in the flue gas reacted with CaO in a sulfation reaction reaction to block the pores, which was not conducive to the capture of As by CaO. The presence of moisture led to poor pore structure collapse of the solid phase products as well as the formation of gehlenite, which reduced the enrichment of As by CaO. DFT calculations showed that the adsorption of As2O3 molecules on the CO2+CaO(001) surface was affected by the position of the O active site, and the adsorption energy at the OC1 top site was higher than that on the clean surface, which was favorable for the stable adsorption of As2O3 molecules. The existence of SO2 decreased As2O3 molecules’ adsorption energy on the CaO(001) surface, which was unfavorable for the adsorption of As2O3 molecules. There were two main effects of H2O molecules on the adsorption of As2O3 on the CaO(001) surface. One was the H2O molecules weakened the interaction between the As atoms and Osurf atoms, which was unfavorable to the adsorption of As2O3 molecules; the other was the existence of stronger adsorption of O atoms in H2O molecules on As atoms in As2O3 molecules, which made As2O3 molecules adsorbed at the top of OH0 adsorbed with adsorption energies much larger than that of clean surface, and the adsorption was more stable.

An Evaluation of the Influence of Meteorological Factors and a Pollutant Emission Inventory on PM2.5 Prediction in the Beijing–Tianjin–Hebei Region Based on a Deep Learning Method

In this study, a Long Short-Term Memory (LSTM) network approach is employed to evaluate the prediction performance of PM2.5 in the Beijing–Tianjin–Hebei region (BTH). The proposed method is evaluated using the hourly air quality datasets from the China National Environmental Monitoring Center, European Center for Medium-range Weather Forecasts ERA5 (ECMWF-ERA5), and Multi-resolution Emission Inventory for China (MEIC) for the years 2016 and 2017. The predicted PM2.5 concentrations demonstrate a strong correlation with the observed values (R2 = 0.871–0.940) in the air quality dataset. Furthermore, the model exhibited the best performance in situations of heavy pollution (PM2.5 > 150 μg/m3) and during the winter season, with respective R2 values of 0.689 and 0.915. In addition, the influence of ECMWF-ERA5’s hourly meteorological factors was assessed, and the results revealed regional heterogeneity on a large scale. Further evaluation was conducted by analyzing the chemical components of the MEIC inventory on the prediction performance. We concluded that the same temporal profile may not be suitable for addressing emission inventories in a large area with a deep learning method.

Potential and health impact assessment of air pollutant emission reduction: a case study of China

Potential and health impact assessment of air pollutant emission reduction: a case study of China

Natural Disaster, Tax Avoidance, and Corporate Pollution Emissions: Evidence from China

Natural Disaster, Tax Avoidance, and Corporate Pollution Emissions: Evidence from China

Pollution Emission Intensity and Domestic Value-Added Rate of Firms' Exports: An Empirical Analysis Based on China’s Microdata

Abstract With the development of global economic integration, global value chains (GVC) have become the mainstay of the global economy. China's low-end embedded model relying on its labor advantage can no longer bring new economic benefits, and the ensuing environmental problems are intensifying. Therefore, there is an urgent need to explore a win-win path for the greening of China's economy and the improvement of GVC status. Using micro-firm data, the article explores the role of pollution emission intensity of China's firms in influencing the domestic value-added rate of their exports. The study finds that (1) the increase of pollution emission intensity of Chinese enterprises has a significant inhibiting effect on their export domestic value-added rate; (2) the pollution emission intensity of Chinese enterprises under different regions, different ownership and different trading methods has differentiated effects on their export domestic value-added rate. Among them, the pollution emission intensity of state-owned enterprises, enterprises in western regions and processing trade enterprises have a more significant inhibitory effect on the domestic value-added rate of their exports; (3) the increase of total factor productivity of enterprises can slow down the negative effect of enterprise pollution emission intensity on the domestic value-added rate of its export. Keywords: Enterprise Pollution Emission Intensity, Export Domestic Value-Added Rate, Global Value Chain Embeddedness.

Policies and tools for climate change policy implementation: a panel data analysis at industrial and commercial level

Climate change is a very debated topic among academia, national and international institutions. Therefore, policies and tools for diminishing pollutant emissions are in place in a number of countries. Among them, taxation and renewable energy use seem to be among the most important. This paper aims at testing the impact of certain tools for climate change policy implementation, such as environmental taxes, renewable energy use, real productivity, employment rate taking into consideration the level of economic development and the GINI coefficient, on the greenhouse gas emissions in two important sectors of the economy: industry and commerce. Panel data analysis is used for a cluster of nine developing countries of the European Union that have the per capita GDP at purchasing power parity lower than 80% of the EU average, during 2008–2021. Similar to other studies, the results show a negative relationship between environmental taxation and greenhouse gas emissions in the industrial sector, and a positive one in the commercial sector. The latter is explained by the fact that transport, which is a main pollutant sector, is also one of the most difficult sectors to achieve green transition, given high associated costs. The analysis also shows that renewable energy use discourages the emissions of greenhouse gases, both in the industrial and commercial sectors, so that fostering investment in renewables is an important factor for addressing climate change and promoting a sustainable growth.

Mixture composition design of magnesium oxychloride cement-stabilized crushed stone materials applied as a pavement base

Conventional binding materials, such as silicate cement and lime, present high energy consumption, pollution, and carbon emissions. Therefore, we utilize crushed stone as a stabilization material. Magnesium oxychloride cement (MOC) is modified and used as an inorganic admixture owing to its eco-friendly nature and low carbon content. We analysed the control indicators of an integrated design of MOC-stabilized crushed stone by conducting unconfined compressive strength and water-resistance tests. The optimum mixing composition of the MOC-stabilized crushed stone was determined through the response surface methodology. We determined the best approach and dosage for improving the water resistance of MOC-stabilized crushed stone by comparing the effects of four modification methods: fly ash, citric acid + silica fume, phosphoric acid + waterborne polyurethane, and dihydrogen phosphate potassium salt. We also perform a comparison with 5% ordinary silicate cement-stabilized crushed stone. The results indicate that the MOC-stabilized crushed stone exhibits a rapid increase in strength in the early stage, but this rate reduces after 28 days. The mixing design employs the 4-day unconfined compressive strength and 1-day water resistance coefficient as the technical indicators. The best mixing composition includes a 4.27% MOC dosage and a molar ratio of MgO/MgCl2 of 5.85. We use 1% citric acid + 10% silica fume in equal amounts to replace the MOC dopant method for composite modification of the MOC stabilized crushed stone. Consequently, the 1-day water resistance coefficient before water immersion is significantly increased from 0.78 to 0.91 and its 4-day unconfined compressive strength is only reduced by 0.10 MPa. This significantly improves the water resistance of the MOC-stabilized crushed stone and ensures that its strength remains unaffected, which is the optimal modification method. However, this method must ensure that a small amount of citric acid and silica fume are uniformly distributed in the MOC-stabilized crushed stone, which increases the construction difficulty of the road base.

Intermodal travel planning and decision support integrated with transportation and energy systems

The fast urbanization in China makes it all the more important to find sustainable solutions that are both comprehensive and energy-efficient. Because of its important role in lowering logistical expenses and pollutant emissions, intermodal transport is generally seen as an effective method of coordinating transportation operations, helping to address the growing economic and environmental issues. Considering the characteristics of a growing city, this article lays out a multi-criteria method for selecting which new initiatives for China's public transportation system should be prioritized. “Electric municipality bus,” “light rail system,” and “modernization to the current fleet and optimization” are the three enhancement initiatives that are outlined. Using transportation-related economic, social, and environmental sub-criteria, this research applies TOPSIS, an analytic hierarchy method and fuzzy approach for order preference by resemblance to ideal circumstance application, to prioritize transportation projects. The study aims to improve city life in Chongqing, China, by identifying the most environmentally friendly development projects. Applying the analytical hierarchy method (AHP), the relative importance of several sustainability criteria was established for use in making strategic decisions. The alternative projects for the given city have been ranked using the fuzzy TOPSIS approach. However, the investigated results show the supportive response of hybrid to environmental sustainability and vice versa for non-hybrid vehicles. However, the energy consumption in public transport remains a leading hurdle in sustainability across the three modes of transport: taxis, rail transit and buses. Finally, computer trains in public transport also surprisingly deal with environmental sustainability to keep the current & forthcoming generation from ecological harm. However, theoretical and empirical policy suggestions have been proposed to become clean & green shortly.

Pollutant Emissions and Heavy Metal Migration in Co-Combustion of Sewage Sludge and Coal

Pollutant Emissions and Heavy Metal Migration in Co-Combustion of Sewage Sludge and Coal