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Assessing air quality with multiple parameters is crucial and demands meticulous analysis due to its profound impact on human health and the environment. Traditional air quality techniques might overlook uncertainties in pollutant data. The fuzzy logic approach adeptly handles such uncertainties. This study thoroughly analyses two approaches: Fuzzy Multi-Attribute Decision Making (MADM) methods and the Fuzzy Inference System (FIS). Fuzzy MADM methods, including the fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and fuzzy VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR), are employed with a combined weighting approach involving Analytical Hierarchy Process (AHP) and Entropy. The FIS approach utilizes the Mamdani method built using MATLAB 2021b’s fuzzy logic toolbox. The air quality is assessed for the Diwali festival for the year 2022 in the various regions of Tamil Nadu, India. Spearman’s rank correlation is utilized to determine the result accuracy of fuzzy MADM and FIS. The fuzzy MADM methods attained a higher correlation of 0.88 compared to the Mamdani FIS of 0.84. Fuzzy MADM proves most effective in air quality assessment.

The air quality is directly related to people’s lives. This paper selects air quality data of Sichuan Province as the research object, and explores the inherent characteristics of air quality from the perspective of complex network theory. First, based on the complexity of network topology and nodes, a community detection algorithm which combines the clustering idea with principal component analysis (PCA) algorithm and self-organization competitive neural network (SOM) is designed (CSP). Compared with the classic community detection algorithm, the result proves that the CSP algorithm can accurately dig out a better community structure. Second, based on the strong correlation distance and strong correlation coefficient of the air quality network, the Sichuan Air Quality Complex Network (SCCN) was constructed. The SCCN is divided into five communities using the CSP algorithm. Combining the characteristics of each community and the Hurst coefficient, it is found that the air quality inside the community has long-term memory. Finally, based on the idea of time-dependent cross-correlation, this paper analyzes the cross-correlation of AQI time series of different stations in each community, constructs a directed air quality cross-correlation network combined with complex network theory, and locates the important pollution sources in each region of Sichuan Province according to the topological structure of the network. The work of this paper can provide the corresponding theoretical support and guidance for the current environmental pollution control.

This study used the contingent valuation method (CVM) to measure the benefits of improved air quality in Metro Manila through the adoption of cleaner public transportation. A single-bound dichotomous choice contingent valuation approach using the referendum format was used to estimate the willingness to pay (WTP) from a survey of 1,000 households. The study arrived at WTP estimates for the proposed program ranging from USD3.85 to USD5.77 per month. Income elasticity of WTP was estimated at 0.49. The study also investigated the impact of using secret ballots for eliciting WTP responses to minimize "yea-saying" behavior and reduce social desirability bias.

Self-similar and generally scaling laws are pointed out in time series issued from different types of data. The analysis of these structures has been conducted via many advanced mathematical tools such as wavelets. In this paper, we propose to exploit some self-similar type models for the modeling of time series issued from air quality and/or pollution data, by using wavelet multifractal techniques. The applied models are shown to involve self-similar, multi-scaling and also noised structures. The resulting models are applied empirically on a sample of data issued from air pollution factors in the northwestern region of Tabuk governorate in Saudi Arabia. Some of the chemicals and materials are essential components of many air pollution factors such as PM10 and PM2.5 particles.

The European Union (EU) legislative framework related to air quality, together with national legislation and relevant declarations of the United Nations (UN), requires an integrated approach concerning air quality management (AQM), and accessibility of related information for the citizens. In the present paper, the main requirements of this legislative framework are discussed and main air quality management and information system characteristics are drawn. The use of information technologies is recommended for the construction of such systems. The World Wide Web (WWW) is considered a suitable platform for system development and integration and at the same time as a medium for communication and information dissemination.

The scope of this paper is to describe the existing problems with respect to the lack of a harmonised assessment approach for air quality, and to provide general recommendations and priorities for an assessment approach at the European scale. Taken that the approach for assessment may diverge among the European countries and the players involved, recommendations are general and aim at providing the overall framework on the basis of which the formulation of specific assessment approaches could be worked out. The starting point for the paper is a synopsis of the characteristics of air quality assessments, as well as of the drawbacks for a harmonised assessment approach at the European scale. The assessment of air quality is then described in relation to sources as well as to effects. At a final stage the assessment goals are recognised and the link between air quality assessment and integrated assessment is also discussed.

What determines the environmental regulatory regime of a country or region? This paper addresses the question in detail, using the US and its widely varying environmental policies as the case study. What factors lead some US states to pass strict environmental regulations, while others are content with the baseline standards required at the national level? This work outlines the state environmental choice as a trade-off between the desires of consumers (who want better environmental quality) and of producers (who want less restrictive environmental standards). A rational state legislator maximises her chances of being re-elected by balancing these two competing forces when setting environmental policy.

I test this model by directly analysing the state decision to adopt more restrictive sulfur dioxide regulations than those required by the federal government under the Environmental Protection Agency's "National Ambient Air Quality Standards" program. The statistical results suggest that legislators weigh the relative influence of consumer and producer groups when setting sulfur dioxide standards, in addition to accounting for meteorological influences that affect the cost of compliance with stricter environmental regulations. Limited evidence is also provided to support an inverted-U shaped relationship between income levels and environmental regulations.

Worldwide, the increasing deterioration in urban air quality due to vehicle emissions has created the need for greater capacity in air quality management and more comprehensive knowledge about the sources and spatial and temporal distribution of vehicle emissions, without which impact studies and subsequent mitigation policy cannot be formulated. To investigate this proposition and assist with the design/development of new air quality information tools for this evolving context, this research examines the generation and use of air quality information in New Zealand, through two case studies. The first case study examines NZTER, a tool used for generating 'vehicle fleet emission rates information' used in a number of different models for air quality assessment and transport policy. The second case examines the early stages of the development and operationalisation of an integrated environmental management tool, the VFEM-w, which hopes to quantify/model the type, source and pathways of airborne pollutants entering the urban stormwater water system. While the NZTER is uncomplicated, it is inefficient and produces information of insufficient quality in the current policy-making context. The VFEM-w case illustrates the challenges of attempting to embed a conceptually and technically complex model in an existing cultural, technical and political setting. Recommendations for the use and development of air quality information tools are made and closing comments consider the issue of information quality in sustainable management.

Policy makers are turning to market-based mechanisms to engender innovative ways of reducing polluting air emissions. As with any emerging market, environmental policies must be carefully crafted so that the institutions and incentives needed to form working markets are developed. Attention must be paid to creating avenues for communities and other "non-moneyed" or unorganised interests to be involved in the new market processes. This paper proposes a strategy to create sustainable, community-based methods to reduce polluting air emissions within the context of market-based incentive programs. By enabling communities to effectively participate in environmental solutions, they will truly be able to "think globally, act locally".

Recently, Chinese megacities have suffered serious air pollution. Previous studies have pointed out that transportation systems have become one of the major sources of air pollution and on-road pollutant concentrations are significantly higher than off-road. Electric vehicle (EV) introduction is proposed as a method to alleviate the current situation. In order to better understand the benefit of the use of EVs in Beijing, a simulation platform has been developed to evaluate the improvement of air quality with the use of EVs quantitatively within the selected area. Four scenarios with different EV penetration rates are proposed and the results revealed 5%, 10%, 15% EV penetration rates which will bring about improvement of 0.86%, 9.01% and 12.23% for PM2.5, 0.92%, 9.01% and 13.32% for nitrogen oxides (NO_x), 0.95%, 8.86% and 13.73% for CO, respectively. The results revealed a promising improvement of air quality with the introduction of EVs.

Addressing the urban heat island effect is critical in mitigating the threat of heat from the perspective of land use planning and design. This paper, therefore, presents a structured review of urban heat island mitigation policy that is contained in the local-level planning policy documents and regulation of 20 large municipalities throughout the United States and Canada. It explores how the issue of the urban heat island effect is framed and approached and, therewith, facilitates an understanding of how aware municipalities are of the issue and its impacts. The review identifies a total of 307 instances of mitigation policy measures among 19 of the 20 municipalities, with the most commonly applied: approaches to mitigation being the promotion of latent heat flux, albedo modification, and provision of shade cover; and, framing contexts being public health, air quality, energy, comfort, and climate change. Although the review indicates that there is widespread awareness of the issue, it notes that only 79, or 25.7 percent, of the 307 mitigation policy measures were framed in any context. Thus, the majority of policy measures do not communicate an understanding of the significance and potential impacts of the urban heat island effect or provide a lens through which it should be perceived and, therewith, addressed. Indeed, they call for blind action. This suggests a need to promote awareness of the potential impacts of the urban heat island effect and communicate same in local planning policy documents and regulations.

In the absence of preventive therapies or effective treatment for most cases of coronavirus disease 2019 (COVID-19), governments worldwide have sought to minimize person-to-person severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission through a variety of lock-down measures and social distancing policies. Extreme events like the COVID-19 pandemic present a tremendous opportunity to make quantitative connections between changes in anthropogenic forcing, social and economic activity, and the related Earth system response. In this paper, we examine the air quality impacts associated with the pandemic response measures in the Northeastern United States.

Global climate change has already had observable effects on the environment. Glaciers have shrunk, ice on rivers and lakes is breaking up earlier, plant and animal ranges have shifted and trees are flowering sooner. Under these conditions, air pollution is likely to reach levels that create undesirable living conditions. Anthropogenic activities, such as industry, release large amounts of greenhouse gases into the atmosphere, increasing the atmospheric concentrations of these gases, thus significantly enhancing the greenhouse effect, which has the effect of increasing air heat and thus the speedup of climate change. The use of sophisticated data analysis methods to identify the causes of extreme pollutant values, the correlation of these values with the general climatic conditions and the general malfunctions that can be caused by prolonged air pollution can give a clear picture of current and future climate change. This paper presents a thorough study of preprocessing steps of data analytics and the appropriate big data architectures that are appropriate for the research study of Climate Change and Atmospheric Science.

Indoor air quality of a public transport interchange station in a comprehensive transit hub has been investigated by experimental studied and numerical simulation. Carbon monoxide was selected as the main pollutant for description of air quality. Ventilation systems, bus traffic and passenger flow have been get by on-site measurement. Large eddy simulation technology has been applied to analyze indoor air quality of public transport interchange station. The boundary conditions are determined according to the measured date. The distributions of carbon monoxide at heights of 0.8m and 1.6m under different time periods and operating conditions of public transport interchange station are calculated. Time periods include the peak hour and trough hour in this study. Results show that carbon monoxide concentration in peak hour is about twice than that in trough hour in most area except the rear area of the vehicle. Air quality would reach the harmful degree in period between 5min to 10min if the ventilation system is not operating. The ventilation system should be operated during the peak hour and intermittent operation mode can be adopted during trough hour in order to meet the requirement of air quality standards.

It is a necessity to introduce sufficient fresh air intake to ensure adequate indoor air quality in a variable air volume (VAV) air conditioning system, however this comes at the cost of heavy wind load. This paper proposes the application of CO2 concentration control in the VAV control system as a measure of indoor air quality and to achieve energy saving operational control of the air conditioning system. The simulation results demonstrate that the proposed scheme is able to balance the energy consumption due to fresh air intake and indoor air quality. Therefore, the dual mode VAV system provides dynamic and steady-state performance, high precision control, and remarkable energy saving effects; and it has wide application prospects.

One of the issues associated with analysing data coming from multiple sources is that the data streams can have markedly different spatial, temporal and accuracy characteristics. For example, in air quality monitoring we may wish to combine data from a reference sensor that provides relatively accurate hourly averages with that from a low cost sensor that provides relatively inaccurate averages over finer temporal resolutions. In this paper, we discuss algorithms for analysing multi-fidelity data sets that use the high accuracy data to allow a characterisation of the low accuracy measurement systems to be made. We illustrate the approaches on data simulating air quality measurements in co-location studies in which a reference sensor is used to calibrate a number of other sensors. In particular, we discuss approaches that can be applied in cases where sensors are outputting averages over different time intervals.

Air pollution causes a wide range of effects on human health, including disorders of the respiratory and cardiovascular systems. Prior knowledge of levels of pollutants in the atmosphere of an area can be useful to provide data to activate emergency actions during periods of atmospheric stagnation, when the levels of pollutants in the atmosphere can represent risk to public health. Hence, the development of an efficient air quality prediction and early warning system is an obvious and imperative need.