Imagining an air quality framework that works: How do we mainstream offsets?

Introduction of local Air Quality Management in South Africa: overview and challenges

Optimal Methodology to Generate Road Traffic Emissions for Air Quality Modeling

Interactions between mathematical and biological sciences have been increasing rapidly in recent years. The use of system analysis and mathematical model for formulation and solving the environmental pollution is of relatively recent vintage and has been used widely since last three decades. These models can be used to conduct numerical experiments, test hypothesis and help to understand the response of environmental pollution. A mathematical model acts as a bridge between study of mathematics and application of mathematics in environmentand other fields. Modeling is an abstraction of reality and its ultimate objective is to explore the complexity of functions and structure of the system under study. Today, a wide variety of models belonging to different nature and category are available to understand the processes of the environment around us. Various models such as WASP, CE-QUAL-ICM, QUAL W2, AQUATOX, QUAL2K, IITAQ, PEARL, GRAM, UGEM, and IITLT etc. related to water and air quality are developed so far along with their principles, intended use and applications. These models generally simulate the basic physical, chemical and biological processes. In the present study, an attempt has been made to evaluate the concept and utilization of mathematical models in air and water quality management.

The rapid economic growth in developing countries has led to increases in energy consumption patterns and industrial activity leading to air quality degradation. Due to the rapid industrial expansion in South Africa, there has been a great demand for increased electrical generation. About 89% of electricity generated in the Southern African Development Community (SADC) region is from coal, mostly produced in South Africa. Eskom generates 95% of the electricity used in South Africa and has undertaken extensive air quality monitoring on a regional basis since the 1970s. The aim of the monitoring is to assist Eskom in the assessment of environmental impacts related to its activities and to facilitate appropriate control strategies. The South African Highveld is impacted by emissions from motor vehicles, heavy and light industry, power stations, coal mining and numerous large townships and informal settlements. This paper presents air quality monitoring and management trends adopted by Eskom for the past 20 years over the Highveld region of South Africa and how these have changed with time. An overview of air quality monitoring methods is presented and ambient air quality trends over a minimum of a 10-year period at specific monitoring stations are discussed. Generally ambient concentrations of pollutants such as sulphur dioxide (SO2), nitrogen oxides (NOx) and fine particulate matter (FPM) have been decreasing with time in the Highveld region. This can be attributed mainly to control strategies adopted by Eskom and to the electrification of households.

The role of environmental management is extremely important in human life because of its contribution to environmental protection and strategies. In modern society, nevertheless, facing the challenges in land, water, and air quality management in reality is unavoidable. Understanding the information on variability and features of environmental issues is necessary to support decision-makers in establishing environmental management planning. Spatial information and data should be considered as basic initial knowledge of environmental management. Among various technologies, Geographic Information Systems (GIS) is known as one of the most popular tools to store, analyze, and visualize data relating to geographically referenced information which can mitigate these challenges more effectively and accurately. The main purpose of this paper is to emphasize how GIS applications in environmental management, discuss the challenges of GIS technology in environmental management, and provide recommendations for future research directions. Many articles over the last decades were reviewed to highlight the application of GIS in environmental management. These results indicated GIS applications support land, water, air quality, and waste management. Moreover, it is a useful tool to monitor and assess environmental quality and in environmental planning and decision-making. For the limitation of GIS application, it is obvious that accuracy assessment and sensitivity analysis should be noticed and assessed although GIS application may strongly support decision-making in environmental management. Emerging GIS technologies and tendencies could help address these challenges. In future, GIS should be integrated along with new technologies and different decision-making algorithms in further steps for developing and supporting spatial decision-support systems more efficiently.

India has a good number of environmental regulations, but these are tangentially touching the core aspect of the issue. Here we have looked into all the environmental regulations in India by analysing the ways in which the environment should be regulated effectively. The command and control (CAC) policies have been critically examined vis-à-vis the market-based instruments. This has been done first by constructing a comprehensive definition of ecotaxes and thus examining the existing taxes in India which could be deemed as environmental taxes in the strict Pigouvian sense. Thereafter, in this study, polluting sectors and goods were identified for the potential levy of ecotaxes in all the three types of pollution, i.e. air, water and land. Finally, the status of the CAC policies and their compliance by the polluting industries were examined by studying the interrelationships between the legislative, executive and judiciary. Fifteen types of environmentally related taxes were identified in India of which only two could be deemed as direct environmental taxes: ‘vehicles tax (on old automobiles)’ levied in Andhra Pradesh, Tamil Nadu, Rajasthan, Karnataka, Goa and Maharashtra and ‘vehicles entry tax’ in Himachal Pradesh and Uttarakhand. The environmental legislations are overlapping, and the powers given to the pollution control boards (PCBs) are insufficient and thus these laws act as toothless tigers. Alert judiciary has played very significant role in protecting the environment in India; however, it is also plagued with delays in the judgements and is constrained with the lack of technical expertise in several environmental pleas because of which the judgements are not pragmatic.

The UK and the EC have recognized that the application of national and EC policies alone may not be cost effective in improving air quality in some areas, especially in traffic-congested urban centres and along major road transport corridors. Consequently both have introduced new strategic frameworksfor air quality management.This paper outlines and compares the UK National Air Quality Strategy (NAQS) and the EC approach, set out in the Air Quality Framework and Daughter Directives. Both frameworks shift responsibility for reviewing, assessing and managing air quality on to local authorities. The UK considers the NAQS will provide the principal means of carrying out its commitments under the new EC framework.Local authorities in the UK have begun the review and assessment phase of the NAQS. This paper examines the support that central government has had to provide to local authorities to ensure the NAQS will be effective. It offers insights into what other Member States are likely to face when implementing their interpretation of the EC air quality management framework. The paper highlights that many UK local authorities lacked even basic air quality management capabilities when the NAQS was being formulated. Consequently the UK Government has had to expand the national pollution monitoring networks (this was achieved primarily by affiliating the growing number of local authority funded sites), commission new detailed urban emissions inventories, and develop and validate a suite of air quality dispersion models. Training events in air quality assessment techniques have had to be offered and many detailed guidance notes issued to ensure an appropriate and consistent interpretation of the NAQS. Some government initiatives to support the implementation of the NAQS suffered delays which initially caused some unnecessary uncertainties and inconsistencies amongst local authorities conducting their review and assessment of air quality. This points to the importance of the Governmentensuring that the support for the management phase of the NAQS will be in place in time. This includes providing additional pollution-control powers and reformulating transport and planning policies in order to integrate air quality management more fully.

Characterisation of ambient air quality over two urban sites on the South African Highveld

We investigate PM2.5 data reliability in five major Chinese cities: Beijing, Shanghai, Guangzhou, Chengdu and Shenyang by cross-validating data from the US diplomatic posts and the nearby Ministry of Environmental Protection sites based on three years' data from January 2013. The investigation focuses on the consistency in air quality assessment derived from the two data sources. It consists of studying (i) the occurrence length and percentage of different PM2.5 concentration ranges; (ii) the air quality assessment for each city; and (iii) the winter-heating effects in Beijing and Shenyang. Our analysis indicates that the two data sources produced highly consistent air quality assessment in the five cities. This is encouraging as it would inject a much needed confidence on the air pollution measurements from China. We also provide air quality assessments on the severity and trends of the fine particulate matter pollution in the five cities. The assessments are produced by statistically constructing the standard monthly meteorological conditions for each city, which are designed to minimize the effects of confounding factors due to yearly variations of some important meteorological variables. Our studies show that Beijing and Chengdu had the worst air quality, while Guangzhou and Shanghai faired the best among the five cities. Most of the five cities had their PM2.5 concentration decreased significantly in the last two years. By linking the air quality with the amount of energy consumed, our study suggests that the geographical configuration is a significant factor in a city's air quality management and economic development.

Poor air quality is one of the main dysfunctions of the rapid urbanisation process in Africa. Although the information is fragmented, the limited evidence available points out that air quality is a leading health risk in Africa, especially affecting the poorest, most vulnerable communities. In this study, we look into five cities in Africa to understand the nature of urban air quality issues and to delve into the initial responses. We report on the status of the main air quality management dimensions, including air quality standards and monitoring strategy/capabilities, emission inventories and air quality modelling, health impact assessment studies, communication practices, development and implementation of clean air action plans (in connection with other relevant strategies, i.e. climate change policies) and governance issues. We find that all cities have limited monitoring capabilities although communication strategies may differ substantially. While indoor pollution sources are declining in more developed economies, traffic is a growing concern in all five cities. In most cases, air quality issues are mostly related to PM2.5 and natural contributions worsen air pollution from road transport, biomass and open waste burning. While nationally-driven strategies, often based on large-scale engineering projects and financial schemes, may report substantial gains in early stages, multi-level governance and planning is likely to maximize benefits and provide a useful framework for the complex problem of air quality management in the long run. The integration of air quality plans in overarching strategies to tackle persistent poverty and social inequity is urgently needed.

What lies beneath?—issues in the representation of air quality management data for public consumption

In 1995 the government finally accepted that local authorities should play a key role in managing air quality, especially with regard to the growing problem of traffic pollution. It proposes a National Air Quality Strategy which requires local authorities to review local air quality periodically. Where air quality standards are not met, local authorities will be expected to designate such areas as Air Quality Management Areas (AQMAs) and to introduce measures to improve air quality over a specified timescale, subject to public consultation and government approval. Local authorities are promised new pollution control powers for AQMAs and the government will consider the resource implications of this new legislation. Whilst there is widespread support for these proposals this paper explores the many practical issues which need addressing and resolving before local air quality management will become effective where populations are at risk from poor air quality.

Air quality forecasting is essential for protecting public health and the environment. The World Meteorological Organization (WMO) has developed initiatives like the Global Air Quality Forecasting and Information System (GAFIS), the Sand and Dust Storms Warning Advisory and Assessment System (SDS-WAS) and the Vegetation Fire and Smoke Pollution Warning Advisory and Assessment System (VFSP-WAS) to enhance forecasting capabilities.   In this context, low-cost air quality sensor systems (LCS) are transformative tools in modern air quality management, offering new opportunities to complement traditional monitoring methods. By integrating LCS data with established systems, such as satellite observations and reference-grade instrumentation, the reliability and applicability of air quality data for forecasting can be significantly enhanced.  A key strength of LCS is their ability to expand the spatial and temporal reach of monitoring networks. However, their use must address inherent limitations in accuracy and precision. Co-locating LCS with reference-grade monitors is essential to quantify uncertainties and ensure data quality. This calibration step enables the deployment of LCS in advanced applications like air quality forecasting. Successfully implementing LCS networks for global, regional, or urban forecasting requires careful planning to ensure adequate spatial coverage, data quality, and timely updates, as well as seamless integration with other systems for actionable insights.   The World Meteorological Organization (WMO) has been instrumental in coordinating global efforts to optimize LCS deployment. Through guidelines, best practices, and integration frameworks, the WMO supports national and regional initiatives to enhance air quality management. A recent WMO report (WMO, 2024) underscores the importance of incorporating LCS into comprehensive monitoring frameworks for supporting air quality forecasting and reanalysis applications.  Ongoing advancements in LCS technology and standardization—led by organizations like WMO —are vital to unlocking their full potential. These efforts promise a more equitable and effective approach to air quality management, ensuring that LCS contribute meaningfully to global strategies for monitoring and forecasting. The present contribution will overview the main outcomes of the WMO’s 2024 report on the use of LCS for air quality forecasting and reanalysis applications. 

Air pollution is a major source of worry for all living things. India has one of the world’s highest levels of air pollution. Rising population, unplanned growth, increased automotive traffic, stubble burning, industrial waste, fossil fuel combustion, powerplant emissions and a variety of other causes all contribute considerably to air pollution in developing countries. Particulate matter (PM) 2.5 is the most concerning of all air pollutants since it causes major health problems in individuals. Prediction and management of air quality have therefore become critical. Several machine learning algorithms were used in this work to examine dataset results. The results of our work suggest that for future predictions, logistic regression and autoregression can be efficaciously utilised for the analysis and forecasting of levels of PM2.5 in the future. Countries can lower the prevalence of strokes, and chronic and acute respiratory illnesses such as asthma, and lung cancer by reducing air pollution levels.

The UK has implemented a system of Local Air Quality Management (LAQM) to tackle the many contemporary sources of air pollution, notably transport, industry and domestic fuel burning, in a holistic manner. The current legislation stems from the Environment Act 1995, which required a National Air Quality Strategy (NAQS) to be published outlining the Governments policies with respect to the assessment and management of air quality. The NAQS, originally published in March 1997, is on a rolling programme of reviews in order to reflect developments in European legislation, technological and scientific advances, improved air pollution modelling techniques and an increasingly better understanding of the economic and social issues involved. Following the first review (currently at consultation stage), this paper will