Deterioration Of Air Quality Research Articles

Utilizing Data Mining Techniques in Geophysical and Biological Analysis for Assessing Environmental Risks

This study aimed to assess environmental risks using data extraction techniques. It focused on geophysical and biological factors and addressed the urgent need for effective risk management strategies to reduce soil erosion, water pollution, and air quality deterioration. A comprehensive dataset was created through the systematic collection of geophysical and biological data including temperature, soil composition, and biological abundance index. It used equipment such as satellite sensors and mountain transmitting stations. Various statistical tools used include decision trees and random forest algorithms. They were used to analyze data and identify important environmental risk factors. The results showed some interesting insights, revealing that the Neural Network has an accuracy of 95.5%, and the Random Forest algorithm predicts risk with an accuracy of 92.0%. It analyzed the classification of environmental hazard zones and identified high-risk zones, such as Zone A, which contains 10,000 people affected by erosion and Zone D, 20,000 people who were at risk from soil contamination. The study concludes that social media can significantly improve understanding and management of environmental risks. Additionally, it provides a useful framework for decision-makers and stakeholders to promote sustainable environmental practices.

Understanding the relationship between land use/land cover changes and air quality: A GIS-based fuzzy inference system approach.

Air pollution is a global issue that demands urgent attention due to its detrimental effects on human health and the environment. Land Use and Land Cover (LULC) change is an essential factor that significantly impacts ambient air quality through alterations in emission sources, vegetation cover, natural processes, and urban design. This study investigates the spatio-temporal variation of key air pollutants resulting from urban LULC changes in the Delhi region. Findings reveal a notable increase in pollutant concentrations, particularly particulate matter, in 2019 (PM10: 318.65 ± 45.80 µg/m3) and 2023 (PM10: 383.70 ± 61.49 µg/m3), compared to 2008 (PM10: 246.76 ± 30.66). LULC change analysis demonstrates a rise in built-up areas 24.59%(2008 to 2019), 33.62% (2008 to 2023) and a decline in vegetation cover 27.49% (2008 to 2019),32.37% (2008 to 2023). Correlation analysis indicates a positive correlation between PM10 and urban indices (+ 0.63) and a negative correlation between PM10 and vegetation indices (- 0.61), highlighting the impact of LULC on air quality deterioration. Subsequently, a fuzzy inference system model integrates LULC information to develop an air quality index (AQI). Incorporating LULC changes in AQI assessment offers a realistic approach to address the complexity arising from combined air pollutant effects, surpassing conventional AQI calculation methods. The findings underscore the significance of understanding the impact of Land Use and Land Cover (LULC) change on ambient air quality in formulating effective air quality management programs and policies. Integrating this knowledge into policymaking is crucial for the successful abatement of air pollution in urbanized areas.

A Delphi study on identifying environmental risk factors in the construction of China-Pakistan Economic Corridor (CPEC)

Abstract The China-Pakistan Economic Corridor (CPEC) represents a monumental initiative aimed at enhancing economic cooperation between China and Pakistan. However, the construction and operational phases of CPEC are fraught with numerous environmental risks that could impede its successful implementation. This study employs the Delphi method to systematically identify and evaluate the environmental risk factors associated with CPEC. A panel of experts from diverse fields, including environmental science, engineering, and regional planning, participated in multiple rounds of surveys to reach a consensus on the most critical environmental threats. Various studies have addressed general environmental impacts of large-scale projects, there is a gap in targeted research that systematically identifies and evaluates specific environmental risk factors associated with CPEC. This study aims to fill this gap by providing a detailed and consensus-based understanding. The findings highlight key risk areas such as carbon emission, climate change, air quality deterioration, and biodiversity loss. By providing a comprehensive risk assessment, this research offers valuable insights for policymakers, stakeholders, and project managers to develop robust mitigation strategies, ensuring the sustainable development of CPEC. The study underscores the importance of proactive environmental management in large-scale infrastructure projects within ecologically sensitive regions.

E-commerce and air pollution: Evidence from China

E-commerce serves as an important link between the digital economy and the real economy, and contributes positively to income growth. In the face of resource constraints and serious environmental pollution, it is equally relevant to examine the environmental effects of e-commerce. Based on county panel data for China from 2011 to 2018, this study uses a difference in differences (DID) model to investigate the impact of Rural E-Commerce Demonstration County (REDC) policy on air pollution. This study reveals that the demonstration policy exacerbates air pollution in counties and the pollution effect is regionally heterogeneous. Additionally, the increase in temperature and precipitation weakens the pollution effects of the demonstration policy. Mechanism analysis indicates that the demonstration policy can promote the development of the secondary industry and digital financial inclusion at the county level, which subsequently leads to the deterioration of local air quality. Further analysis of costs and benefits reveals that the significant positive economic effects resulting from the demonstration policy far outweigh the indirect economic losses caused by air pollution. Therefore, when local governments actively promote the development of e-commerce in rural areas, they should also attach great importance to its potential negative environmental externalities.

About Air Quality Assessment using Time Series Analysis Techniques on Air Particles Data

This study investigates the dynamics of air pollution caused by particulate matter (PM10 and PM2.5) in Omsk, Russia. Data collected from the Sensor.Community network between 2021 and 2023 were analyzed using time series analysis methods. The findings reveal a subtle weekly seasonality in the data, potentially attributed to fluctuations in industrial activity and traffic patterns throughout the week. Additionally, a concerning trend of deteriorating air quality was identified, characterized by increasing annual average concentrations of PM10 and PM2.5. The study employed various time series analysis techniques, including Empirical Cumulative Distribution Function (ECDF), Seasonal and Trend decomposition using Loess (STL), and autocorrelation function (ACF) analysis. These methods allowed for the visualization and examination of data distribution, trend identification, and seasonality detection. Furthermore, the Mann-Kendall test confirmed a statistically significant trend of increasing pollution levels over the three-year period. To enhance the accuracy of spatial analysis, data interpolation was performed using kriging with a Gaussian model. This method, compared to simple interpolation, provides a more precise assessment of the spatial distribution of pollutants. The study also implemented Long Short-Term Memory (LSTM) for forecasting hourly pollution values. LSTM exhibited promising results, demonstrating its potential for developing early warning systems, particularly when combined with meteorological data such as wind forecasts. The results highlight the need for effective measures to mitigate air pollution in Omsk and emphasize the importance of utilizing data from diverse sources, including official air quality monitoring stations, to ensure accuracy and reliability in air quality assessments.

Modeling Civil Aviation Emissions with Actual Flight Trajectories and Enhanced Aircraft Performance Model

Aviation emissions are continuously increasing along with the rapid development of air transportation, and results in the deterioration in regional air quality and the global climate. Accurate emission estimation is of great importance for relevant policies promotion and the sustainable development of the environment. Previous studies focused on the total emissions of a flight and lacked high precision in both spatial and temporal resolutions, especially aviation activities near ground. In this research, we propose an open-sourced emission calculation framework based on actual flight trajectories (TrajEmission), which calculates both the ground and airborne emissions simultaneously according to the configuration parameters, trajectory characteristics, and ambient conditions. We compare the emission results with five emission inventory methods. The results indicate that pollutant (nitrogen oxides, carbon monoxide, and unburned hydrocarbons) emissions in the landing and takeoff (LTO) cycle might usually be underestimated due to a lack of trajectory-based methods. In addition, in the overall results, the method based on the great circle route leads to an overestimation of 56.8% of pollutant emissions compared to the method based on actual routes. We also investigate the extent to which other factors could influence the emission results. To summarize, the TrajEmission framework can build inventories for the whole process of flight movements with high spatial–temporal resolutions and provide solid data support for environmental science and other related fields.

Comprehensive analysis of particle emissions from miniature turbojet engine

Emission of particulate matter from jet engines contribute to deterioration of air quality in the vicinty of the airports and to formation of contrails in higher layers of the atmosphere. This article presents the results of the measurements of particle emissions from a miniature jet engine GTM-120 fueled conventional aviation fuel Jet A-1. Analysis of particle size distribution, number, mass and volume emission indexes has been made, as well as the analysis of the emission intenisty and mass emission rate. Obtained results were related to LTO cycle phases. The results shows, that the particle number concentration was the lowest for low engine loads, with characteristic diameter of 69.8 nm and the particles concentration of 7.7 x 106 particles/cm3. For thrust increase, the characteristic diameter is smaller, and the particles distribution is no longer single-mode. The highest particles concentration for cm3 is for 100% thrust and is equal to 1.55 x 107 particles, with characteristic diameter of 34 nm.

Ethanol recognition based on carbon quantum dots sensitized Ti3C2Tx MXene and its enhancement effect of ultraviolet condition under low temperature

The deteriorating air quality makes it particularly important to detect all kinds of harmful gases in the air. In this study, the Ti3C2Tx MXene/CQDs composite was formed by modifying carbon quantum dots (CQDs) to the surface of Ti3C2Tx MXene, in which the Ti3C2Tx MXene sensitized by CQDs achieved enhanced recognition of ethanol. After a series of characterizations, it was confirmed that CQDs were indeed modified on the surface of Ti3C2Tx MXene. The gas sensing test results show that the sensor based on Ti3C2Tx MXene/CQDs composite exhibits excellent response performance to ethanol, particularly achieving a high response value of 15.38–50 ppm ethanol at the optimal operating temperature of 140 °C. Furthermore, this composite also demonstrates excellent repeatability and a stable response relationship towards ethanol. Finally, it is found by comparison that the recovery time of the sensor under ultraviolet (UV) irradiation is significantly shortened, which further verifies that the sensor has wider application potential under UV condition. The experimental results show that the Ti3C2Tx MXene/CQDs composite significantly improves the efficiency and ability of detecting ethanol by optimization of photoresponsive performance, enhancement of electrical conductivity, and increase in specific surface area. This paper provides practical research methods and ideas for the development of novel sensors based on CQDs and Ti3C2Tx MXene.

-temporal variability in fire events due to crop residue burning and their impact on atmospheric variables using ground and remote sensingdata in Punjab

We attempted monitoring and mapping of the active fire events in Punjab, during the wheat and rice harvesting period of 2017-2021 from the Visible Infrared Imaging Radiometer Suite (VIIRS) at 375 m aboard. The analysis showed that the highest fire counts were observed in the central region, followed by the south-west and thelowest in the north-east region of Punjab during all the years. Moreover, during the wheat season, highest fire counts were observed in 2019, being 2535, 11062 and 6212 in north-east, central and south-west regions, respectively. However, during rice, highest fire counts were observed in 2020 in the north-east being 2857 and in 2021 the central and south-west regions being 40960 and 30351 respectively. In line with the number of fire counts, the highest concentration of gases and particulate matter obtained from the Central Pollution Control Board (CPCB) was also observed in the central zone. During the wheat harvesting season, central zone experienced the highest concentration of PM2.5 and PM10 in May 2018 and that of SO2 and O3 in May 2019. Similarly, during the rice harvesting season, central zone also experienced the highest concentration of PM2.5 and PM10 during November 2017 and that of SO2 in 2018. However, the highest concentration of NO2 was observed in October 2018 and that of O3 in October 2020 in the central region. Analysis of the concentration of NO2 and SO2 obtained from the Soumi-NPP satellite also had similar results to CPCB. Such a high concentration of gases and particulate matter might be attributed to crop residue burning a significant positive correlation was observed between fire counts and concentration of particulate matter (PM2.5 and PM10). In view of the alarming deterioration of air quality, there is a dire need to check this practice in the region by providing incentives and viable alternatives to the farmers.

Mapping PM2.5 Sources and Emission Management Options for Bishkek, Kyrgyzstan

Harsh winters, aging infrastructure, and the demand for modern amenities are major factors contributing to the deteriorating air quality in Bishkek. The city meets its winter heating energy needs through coal combustion at the central heating plant, heat-only boilers, and in situ heating equipment, while diesel and petrol fuel its transportation. Additional pollution sources include 30 km2 of industrial area, 16 large open combustion brick kilns, a vehicle fleet with an average age of more than 10 years, 7.5 km2 of quarries, and a landfill. The annual PM2.5 emission load for the airshed is approximately 5500 tons, resulting in an annual average concentration of 48 μg/m3. Wintertime daily averages range from 200 to 300 μg/m3. The meteorological and pollution modeling was conducted using a WRF–CAMx system to evaluate PM2.5 source contributions and to support scenario analysis. Proposed emissions management policies include shifting to clean fuels like gas and electricity for heating, restricting secondhand vehicle imports while promoting newer standard vehicles, enhancing public transport with newer buses, doubling waste collection efficiency, improving landfill management, encouraging greening, and maintaining road infrastructure to control dust emissions. Implementing these measures is expected to reduce PM2.5 levels by 50–70% in the mid- to long-term. A comprehensive plan for Bishkek should expand the ambient monitoring network with reference-grade and low-cost sensors to track air quality management progress and enhance public awareness.

Research on the Impact and Strategy of the Accelerating Urbanization in China

As urbanization accelerates at an unprecedented pace, especially in rapidly developing nations like China, a range of significant challenges has emerged. This essay will explore four major issues arising from urbanization: polarization, urban planning difficulties, pollution, and global warming. These problems not only impact rural and urban areas but also pose serious threats to the global community. Polarization exacerbates income inequality, leading to a widening gap between rural and urban populations. Urban planning issues, such as inadequate infrastructure, strain city resources, causing congestion and inefficiency, pollution, fueled by industrial growth, deteriorates air quality, posing health risks to citizens; while global warming, driven by increased carbon emissions, accelerates climate change with severe consequences worldwide. To address these challenges, solutions such as boosting farmers incomes, constructing viaducts and taller buildings, promoting the use of masks, and reducing carbon emissions are proposed. However, the feasibility of these solutions depends on each countrys financial capacity and available resources. Therefore, this essay will assess the practicality of these measures and their potential to mitigate the risks associated with rapid urbanization.

Air Cleaning Plants

Air quality, both outdoor and indoor, is the most critical element that we must protect for the entire environment. While the deterioration of air quality primarily causes respiratory diseases in living things, it also causes corrosive effects on nonliving things, such as corrosion caused by acid rain, which results from air pollution. Therefore, it is necessary to monitor and prevent air pollution by various methods. WHO plays an active role in protecting air quality through its mission. Plants are indispensable beings for the environment and life. They balance the CO2 concentration, temperature, and humidity in the air. Plants use CO2, light, and water during photosynthesis, which is necessary for their growth and development. They reduce the CO2 concentration in the environment. In addition, plants, depending on their leaf characteristics, can trap particulate matter in the atmosphere. Many studies have proven that plants positively affect indoor and outdoor air quality. In this review, we aim to summarize the results of some selected studies, provide information about the air purification capacities of the researched plants, and emphasize the topic's importance.

Recent Advances and Implications for Aviation Emission Inventory Compilation Methods

With the rapid development of industrialization and urbanization in China, civil aviation plays an increasingly important role in the transportation industry. However, pollutants and greenhouse gas (GHG) emissions from civil aviation are becoming an increasingly concerning environmental problem. In order to mitigate the resulting environmental pollution, such as air quality deterioration, regional and global climate warming, and declining human health, more and more efforts have been devoted to reducing both pollutants and GHG emissions. Among these efforts, emissions inventories from civil aviation provide a basis for quantifying pollutants and GHG emissions, establishing evaluation standards of environmental impact, and formulating management policies for both air quality improvement and climate change mitigation. In this paper, we reviewed both compilation approaches and data collection methods for civil aviation emissions inventories, introduced several typical calculation methods for aviation emissions inventories, and analyzed specific cases of actual application based on typical methods of inventory compilation. We also described in detail the activity level and emission index calculation methods of several pollutants and greenhouse gases. Furthermore, based on the above research methods, four typical application cases were investigated, including a specific airport, the landing and takeoff (LTO) cycle of a nation, the entire period with the LTO cycle and the climb–cruise–descent (CCD) phase of a country, and global emissions inventories from civil aviation. The results suggest that, in addition to quantifying the emissions of both pollutants and GHG produced by civil aviation, the selection of inventory compilation methods is likely to be important for improving aviation emission inventory accuracy and for further reducing the environmental, economic, and health impacts resulting from aviation emissions. Moreover, this paper can also provide a reference and theoretical basis for the development of aviation emission inventory compilation methods in the future.

Long term analysis of air quality parameters for Ludhiana, India: sources, trends and health impact.

Ludhiana, a pollution hot spot in North India, has seen a rapid deterioration in air quality over the years due to urbanization and industrialization. This study interprets the variations of particulate matter (PM) and gaseous pollutants (Nitrogen oxide, Nitrogen dioxide, NOX, Sulphur dioxide, Carbon monoxide, Benzene, Toluene, Ozone, and Ammonia) for the data observed from 2017 to 2023 in Ludhiana. This also covers the analysis focused on capturing the changes that occurred at the times of lockdown imposed during the Coronavirus Disease (COVID-19). The maximum 24-h averaged mass concentration values exceeded the National Ambient Air Quality Standards (NAAQS) of 100µg/m3 for PM10 concentration and 60µg/m3 for PM2.5 concentration in 2018 by the factor of 5 and 8. With the onset of the COVID-19 lockdown in 2020year, PM10 and PM2.5 reached the minimum level while CO, T, O3, and NO2 increased by the factor of 3.9, 1.9, 1.4, and 1.3 from their previous year. This NO2 is a precursor of ozone formation, a higher NO2 to NO ratio observed during the lockdown, confirms the role of nitrogen compounds in the higher ozone formation rate. Based on the NO2/NO ratio, the probability rate of ozone formation determined using survival analysis is observed to be 94% from 2017 to 2023. The local sources' contribution to these air pollutants during Pre-Lockdown, Lockdown, and Post-Lockdown are analyzed using principal component analysis. The impact of the lockdown on ozone concentration sources has been observed. During the Pre- and Post-Lockdown phases, three sources (PC1, PC2, and PC3) were positively identified. Ozone levels are linked to PC3 in these phases, but during the lockdown, a negative loading in PC3 and positive loadings in PC1 and PC2 indicate a decrease in ozone from reduced emissions and an increase from secondary reactions involving nitrogen compounds. Moreover, the Toluene to Benzene concentration ratio is > 2, indicating the source of their origin from industrial emission or other non-traffic sources. Health assessment for the years 2017-2019 reveals a significant decrease in the number of cases of all-cause mortality, ischemic heart disease, stroke, and chronic obstructive pulmonary disease associated with reducing PM2.5 concentrations to national and international standards.

Application of AERMOD dispersion model for assessment PM10 concentrations from mobile sources in Kuala Lumpur Metropolitan City, Malaysia.

Deterioration of air quality in Kuala Lumpur caused by mobile sources and traffic-related activities with interaction with climatic conditions and dispersion in the atmosphere. This study was focused on predicting the averaged 1-h concentration of particulate matter (PM10) that was emitted from private cars in Kuala Lumpur by applying the air dispersion model American Meteorological Society (AMS)/United States Environmental Protection Agency (EPA) Regulatory Model (AERMOD) in 2014. The AERMOD model indicates that private cars in Kuala Lumpur recorded 1-h concentration of PM10 below the Malaysian Ambient Air Quality Guidelines (RMAQG) in 2014. The highest concentration was 59.2µg/m3 in 2014 and mainly concentrated around the city center and highway networks. The highest concentrations are recorded in early morning and late at night, with the highest concentrations at 4 am and 2 am and 48.68µg/m3 and 38.42µg/m3, respectively. Late night to early morning is identified as the dominant time interval for pollutant dispersion. The findings demonstrated that air quality had a significant impact on the 1-h concentration of PM10 emitted from private cars in Kuala Lumpur.

Understanding the online restaurant rating bias induced by air pollution and the underlying spatial and temporal effects

Using unique restaurant review data in the urban tourism system combined with air quality data in the Chinese context, we confirmed the air pollution-induced mood misattribution in terms of negative online restaurant rating bias. Further heterogeneity analyses grounded in expectancy-disconfirmation theory were conducted. Tests regarding air quality differences across geography (i.e. the spatial effect) show that good air quality in the city where a restaurant is located can induce a stronger online rating bias. Tourists, especially those who are from cities with poor air quality, tend to post biased online restaurant ratings on polluted days compared with their local peers. For locals, their online restaurant rating bias is additionally determined by air quality differences over time (i.e. the temporal effect), suggesting the significance of persistent air pollution rather than by air quality deterioration. Overall, our work highlights the importance of air pollution, an external environmental stimulus, in shaping consumers’ online rating bias towards restaurant services. This underscores the need for guidelines by regarding air pollution that inform sustainable urban planning and destination management.

Quantifying the impact of urban trees on air quality in Geneva, Switzerland

Atmospheric pollution threatens human health worldwide, with tropospheric ozone (O3) and particulate matter (PM) among the most harmful pollutants. Urban trees can reduce the concentration of air pollutants through dry deposition on their canopies and stomatal uptake. At the same time, urban trees can deteriorate air quality by emitting aerosol- and O3 precursors in the form of biogenic volatile organic compounds (BVOCs). O3 and PM removal, and BVOC emissions vary depending on the tree species. Therefore, the diversity and spatial distribution of urban trees significantly influence their impact on local air quality. This study employs a dual approach to assess and map the impact of urban trees on air quality in Geneva, Switzerland. Firstly, we use the i-Tree Eco model combined with a tree inventory (237,191 trees) to quantify BVOC emissions and PM10 (PM < 10 µm) and O3 removal at the genus level. Secondly, we develop a species-level parameterization using 51 common urban tree species to estimate the same variables and ozone-forming potential (OFP). Results show that the tree density is heterogeneous in the study area, leading to neighborhoods with greater biomass and, therefore, stronger influence by trees on local air quality. According to i-Tree Eco, urban trees in Geneva emitted 50 t of BVOCs, while removing 14 t of PM10 and 52 t of O3 in 2014. With the species-level parametrization, we estimate that urban trees removed about 66 ± 55 t of PM10 and 150 ± 96 t of O3 in 2014. However, they could also emit about 130 ± 52 t of BVOCs annually, which, under favorable conditions, can form 1153 ± 519 t of O3. Depending on the method, urban trees removed between 4 and 19 % of the anthropogenic PM10 emissions. The annual removal rates are comparable to findings in other European cities. The disparities between the two approaches are due to different parameterizations. This study could help urban planners to select adequate species for future planting programs in Geneva and more generally. It showed that the impact of urban trees on air quality is spatially heterogeneous but significant, and tightly linked to the species composition.

Microplastics in the Atmospheric Deposited Dust Collected from Different Traffic Intersections in Dhaka City

Plastic particles less than 5 mm in size, known as microplastics, can infiltrate the environment from a variety of sources. This study aimed to assess the presence of microplastics (MPs) in the atmosphere at fifteen major traffic intersections in the greater Dhaka city from July to August 2022.The deposition rate (DP) of MPs was calculated and the observed DPs value ranged from 1.11×106 MPs/m2/day to 5.78×106 MPs/m2/day with a portion of microplastics exhibiting fluorescence activity. Fourier Transform Infrared (FTIR) spectroscopy was used to analyze the functional groups present in microplastics. The identified polymer compositions of MPs were polyethylene (PE), Nylon-6 and natural polymers (cellulose and rubber). The current study highlights the data and knowledge gaps on the atmospheric transport of microplastics and their impact to the deterioration of overall urban air quality. Dhaka Univ. J. Sci. 72(2): 07-14, 2024 (July)

Dynamic Complexity of a Discrete-time Prey-Predator Model with Mixed Functional Responses

Plastic particles less than 5 mm in size, known as microplastics, can infiltrate the environment from a variety of sources. This study aimed to assess the presence of microplastics (MPs) in the atmosphere at fifteen major traffic intersections in the greater Dhaka city from July to August 2022.The deposition rate (DP) of MPs was calculated and the observed DPs value ranged from 1.11×106 MPs/m2/day to 5.78×106 MPs/m2/day with a portion of microplastics exhibiting fluorescence activity. Fourier Transform Infrared (FTIR) spectroscopy was used to analyze the functional groups present in microplastics. The identified polymer compositions of MPs were polyethylene (PE), Nylon-6 and natural polymers (cellulose and rubber). The current study highlights the data and knowledge gaps on the atmospheric transport of microplastics and their impact to the deterioration of overall urban air quality. Dhaka Univ. J. Sci. 72(2): 15-24, 2024 (July)

Assessment of the Efficiency of the Financial Mechanism of Environmental Management

Abstract In recent decades, cataclysmic events, deterioration of air and water quality, and loss of biodiversity have forced us to look for ways to save nature. One of the ways to solve the problems is to ensure rational environmental management, which is possible by establishing an effective balance between consumption and compensation by creating an effective financial mechanism. The purpose of the study is to assess the efficiency of the current financial mechanism for environmental management in Ukraine and to determine the prospects for its improvement. The study uses analysis, synthesis, specification, systematization, and generalization. The graphical method was used to assess environmental taxes, and mathematical modelling was used to analyze the dependence of emissions on direct costs and capital investments in air protection and climate change. Environmental taxes in Ukraine are an ineffective instrument of the financial mechanism of environmental management. Their share in the structure of domestic GDP is lower than the share in the EU. The author suggests ways to improve them: to replace the CO2 tax with an energy tax; to cancel the tax-free limit of 500.000 tons of CO2 emissions per year; to change the structure of tax distribution; to introduce tax rebates. The correlation and regression analysis of the dependence of air pollutant emissions on current expenditures and capital investments in air protection and climate change issues showed the existence of a feedback loop. Investment support for environmental management should be provided from various sources in the following areas: national, local and international finances - primarily for the restoration of air, water and contaminated areas; own funds and international investments - for the modernization and greening of production.