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We are witnessing an explosion in carbon calculators for estimating the greenhouse gas (GHG) emissions (i.e., carbon footprint) of households, buildings, cities, and processes. Seeking to capitalize on the emergent 'green' consumer, corporations are leading the next iteration in carbon footprinting: consumer products. This potentially lucrative low-carbon frontier, however, faces steep challenges due to complexities of scale, largely a function of the number of actors and geographies involved in globalized commodity and energy networks, and scope, which increasingly demands inclusion of emissions due to land use change (e.g., biofuel production, timber harvest, livestock grazing, mining). Life cycle assessment (LCA)-the principal method behind product-level GHG emissions footprint protocols-frequently avoids these challenges by narrowly delineating system boundaries, thereby excluding the 'messiness' of space and place. Through a comparative model of energy sources and emissions in the globalized paper industry, this article reveals how complexities associated with geographic variation and land use change create indeterminacy in footprints based on these protocols. Using industry and trade data, the authors develop geographic information system transportation and energy models to map the globally dispersed pulp supply networks and to rescale Intergovernmental Panel on Climate Change GHG inventory guidelines to include carbon loss associated with land use change in the carbon footprint of coated paper. Given their integrative abilities to conceptualize and model coupled human-ecological systems, sophisticated understanding of time-space dynamics and critical theoretical insights, geographers have much to contribute to the LCA and product carbon footprinting enterprise, which to date has been largely the intellectual domain of engineers. [ABSTRACT FROM AUTHOR]

The American Iron and Steel Institute (AISI) gathered data between 1989 and 1997 to build an "objective database" to further understand the occupational exposures generated by the few asbestos-containing materials remaining at various steelmaking companies at this time. This paper analyzed the 520 samples from this campaign which occurred at five different steel manufacturers: Georgetown Steel Company, Inland Steel Company, Ling-Temco-Vought (LTV) Corporation, United States Steel Corporation, and Weirton Steel Corporation. This database is believed to have never previously been systematically organized. Samples were grouped based on sampling times to determine whether they should most appropriately be compared to the OSHA short-term excursion limit (EL) or the 8-hr time-weighted average (TWA) permissible exposure limit (PEL). Sampling times of 30 min or less were considered short-term samples, and samples of 180 min or greater were considered representative workday samples. Samples that did not fit into either category, with sampling times between 31 and 179 min, were considered task samples. Overall, the data indicated that the airborne concentrations were quite low in 1989 and they continued to be low through the study period which ended in 1997. Only seven out of 286 (approximately 2.5%) short-term or representative workday samples were in exceedance of the current OSHA OELs that were implemented in 1994 (short-term samples being compared to the 1 f/cc EL and representative workday samples being compared to the 0.1 f/cc 8-hr TWA PEL). Consistent with prior data, analysis of this dataset supports the view that materials containing asbestos were not used in many applications in the steel industry, and measured airborne concentrations of asbestos were almost always below the occupational exposure limits (OELs) in the post-OSHA era (1972–2000). [ABSTRACT FROM AUTHOR]

Several coal-fired power plants (CFPPs) were built in South Africa, mainly in the central Mpumalanga Province, due to an increase in the demand for Eskom, the national power utility, to keep up with socio-economic growth. The CFPPs, of which 90% are owned by Eskom, generate a significant share of the country’s electricity but contribute to the air pollution experienced in the country. The paper discusses sulphur dioxide (SO2), nitrogen dioxide (NO2) and particulate matter of size less than 10 micrometre (μm) in diameter (PM10), using data from 2014 to 2018. The statistics revealed higher PM10 concentrations during winter than in summer and spring at the Kriel and Komati sites; associated with the higher contribution of domestic burning. The study’s results could influence legislation and policies and help to understand the source of poor ambient air quality by assessing the three pollutants within the area of the selected power plants. [ABSTRACT FROM AUTHOR]

Air pollution has caused many risks to people, but little research has been done on the effect of residents' air pollution risk perception on their subjective well-being. In order to reveal their relationship, this paper divides air pollution risk perception into four dimensions: risk controllability, risk trust, risk acceptability and risk effect, and explores the effects of different dimensions of air pollution risk perception on subjective well-being based on the structural equation model. The results show that risk controllability, risk trust and risk acceptability can improve well-being, while risk effect can reduce well-being, and air quality satisfaction plays a mediating role. There are also internal influencing mechanisms among different air pollution risk perceptions. Particularly, in areas with poor air quality, risk controllability had a negative association with air quality satisfaction, and higher risk effect corresponded to a higher degree of risk controllability. This paper provides some suggestions for environmental management from the perspective of risk perception. [ABSTRACT FROM AUTHOR]

Since 2010, the Chinese government has developed several batches of low-carbon pilot provinces and cities continuously. And in the backdrop of carbon peak and carbon neutralisation recently, the carbon emission reduction policies and achievements of China have attracted more and more worldwide attention. In the field of human health, this paper investigates whether the Low-carbon Province Pilot Policy of China has positive effects on residents' health based on the micro data of China Family Panel Studies (CFPS) from 2010 to 2016. Using the time-varying difference-in-difference model to solve the endogeneity problem commonly faced in the literature, we find that Low-carbon Province Pilot Policy has a positive impact on public health through air quality improvement and the unemployment level alleviation mainly. And in urban areas, the policy effect is more obvious than that in rural regions. This paper expands the content of national low-carbon governance effects to residents' health further and contribute to China's low-carbon development. Specifically, it reminds us to focus on the dynamic adjustment and effective continuation of the policy, and also the all-round support for 'the disadvantaged' in environmental governance process. [ABSTRACT FROM AUTHOR]

This paper presents interval estimation for the population mean and coefficient of variation in a two-parameter exponential distribution. The new generalized pivot, profile likelihood function and likelihood ratio statistic are derived and used to construct the confidence intervals. A highlight of this paper is that the generalized and likelihood ratio confidence intervals for the mean and coefficient of variation perform well in terms of coverage probability in many cases. Finally, two real-data applications on the air pollution of particulate matter (PM2.5) and the renewable energy through wind power of Thailand are used for illustration purposes. [ABSTRACT FROM AUTHOR]

In the electrostatic precipitation of microparticles, it is common to evaluate the voltages between the corona onset voltage and the breakdown point. However, the charging of particles in the nanoscale size range mainly occurs by diffusion, suggesting the possibility of its occurrence, even at low values. This paper investigates the implications of a wide range of electric fields applied in the collection of nanoparticles (6.15–241.4 nm). Two electrostatic precipitators (P.I. and P.II.), both with plates 10 cm high and 30 cm long, but with different plate spacings (4 and 6.5 cm), were tested using three air velocities (1.9, 2.9, and 3.9 cm/s) and 36 electric fields (0.0 − 5.0 kV/cm). Under the highest electric fields, both precipitators showed efficiencies above 99.9%. Furthermore, nanoparticles were collected before the corona onset voltage, with efficiencies of around 28% (P.I.) and 35% (P.II.). Even though no current was detected by the high voltage source, charges on the particles were measured in electric fields lower than 3.0 kV/cm. The higher the applied voltage, the higher the residual charge of the particles at the precipitator outlet. It is expected that the findings of this work should contribute to the technological development of electrostatic processes for air treatment. [ABSTRACT FROM AUTHOR]

Electric vehicles (EVs) have emerged as a promising solution to address environmental concerns and transform the transportation sector. This paper examines the state-of-the-art EVs, encompassing their history, definition, and different types. The advantages and limitations of each type are compared and contrasted, providing insights into their unique characteristics and potential applications. Critical components of EVs are thoroughly analyzed. The paper explores various types of batteries, emphasizing their features and potential for improving energy density, range, and charging capabilities. Charging infrastructure is discussed, highlighting the importance of establishing a robust network of charging stations. The impact of EVs on power grids is examined, emphasizing grid integration, load management, capacity upgrades, and power quality. Challenges and barriers hindering the wide adoption of EVs are identified, including technological limitations, infrastructure constraints, economic considerations, consumer perception, and policies. The paper delves into the environmental and economic impacts of EVs, including lifecycle analysis, air pollution reduction, and cost-effectiveness. Thus, the paper provides valuable insights into the current state of EVs and their potential to shape the future. The findings highlight the need for collaborative efforts from industry stakeholders, governments, researchers, and consumers to overcome challenges and accelerate the transition to a sustainable transportation system. [ABSTRACT FROM AUTHOR]

Debates about how best to support students' transition from school to university have re-emerged periodically since at least the 1970s. This paper focuses upon one aspect of this transition: how to develop the quantitative skills students acquire at school throughout the first year of their degree. We report on an attempt to inject pedagogic innovation into the teaching of quantitative methods to first-year geography undergraduates at a large Russell Group university in the UK. More specifically, we report on moving to a pedagogic approach of student-centred, inquiry-based learning, which uses quantitative methods to investigate the issue of air pollution. We explore whether "statistical anxiety" is still a common experience of undergraduate geographers and the extent to which pedagogical innovation can help to alleviate this. Although the focus is on UK Geography, the paper has wider relevance to anywhere geographical research methods are taught. [ABSTRACT FROM AUTHOR]

This paper argues that Kim Cho-yeop's science-fiction novel The Greenhouse at the End of the Earth (2020) reveals "trans-corporeal" material and ethical entanglement through its representation of a plant and a cyborg. The "mossvana" plant is genetically manufactured by a cyborg to resist and reduce the destructive effects of a human-induced environmental disaster. The plant is able to withstand the devastation of human-caused "dust," which decimates entire human, animal, and plant populations in the mid-twenty-first century. In this post-apocalyptic novel, the plant emerges not only as the nexus of human and non-human agencies, but also as a figure for human ethical commitments toward non-human others. Through tracing recent trends in the environmental humanities and building on Stacy Alaimo's thesis of "trans-corporeality," this paper argues that this post-pandemic novel reveals a new kind of ethics that fosters inter-species awareness and human-nonhuman connection. In the concluding section, I discuss air pollution in Korea and the metaphoric associations with breathing. I argue that breathing is also a "trans-corporeal" act that transports microscopic particles from the external environment into the human lungs and bloodstream. Breathing is a trans-corporeal act in both the material and ethical senses of the term. [ABSTRACT FROM AUTHOR]

Traffic and production restrictions are two important emergency measures for controlling urban air pollution. The lockdown policies implemented during the COVID-19 pandemic period are nearly equivalent to the policies of traffic and production restriction, which provides a rare opportunity to quantitatively evaluate the effectiveness of these emergency measures. Taking Wuhan, China as the study area, this paper firstly verified the changes in six air pollutants and analyzed their change rules in different lockdown periods using statistical methods. Then the structural breakpoints in air pollutants were detected via regression discontinuity design model. To comprehensively understand the effects of restrictions on air pollution, the influences of meteorological conditions on air pollution were also investigated. The results illustrated that the concentrations of PM2.5, PM10 and NO2 decreased significantly during lockdown period. By comparing with the RDD coefficients of PM2.5 (−34.46), PM10 (−37.11) and NO2 (−19.15), the lockdown had little effect on CO (−0.32). The traffic and production restrictions had no apparent effects on SO2. Although O3 showed an increasing trend, the increase was not limited to the lockdown period, meaning that the traffic and production restrictions had less effect on the increasing trend of O3 concentration. Moreover, the structural breakpoints were verified in four air pollutants (PM2.5, PM10, NO2, and CO), and the structural breakpoints were caused by lockdown instead of the Spring Festival. The results also indicated that the meteorological conditions were not the main reasons for the changes in air pollutants during the lockdown period. This paper reveals how the traffic and production restrictions affect urban air pollution and provides a strong implementation basis for the air pollution control policy. Implications: The traffic and production restrictions are two important emergency measures for controlling heavy urban air pollution. However, these two measures have never been implemented in a large area like a city for a long enough period, so the effectiveness of these two measures has never been estimated quantitatively at a city level. The lockdown policies implemented during the COVID-19 pandemic are nearly equivalent to the policies of traffic and production restriction, which provides a rare opportunity to quantitatively evaluate the effectiveness of these emergency measures. Thus, this study measured the effectiveness of production and traffic restrictions on different air pollutants. This study provides the following implications: (1) the dominant factors for air pollution changes during the lockdown are traffic and production restriction instead of meteorological conditions; (2) the production and traffic restriction policies are effective for reducing concentrations of PM2.5, PM10 and NO2, while having less effect on O3 and CO concentrations; (3) the sharp changes in air pollutants in 2020 are unlikely to be caused by the Spring Festival. These findings are crucial for making more comprehensive policies for protecting urban air quality. [ABSTRACT FROM AUTHOR]

While the problem of Delhi's air pollution is well recognized, as is the class bias of the judiciary in targeting certain sources of air pollution over others, what is less will understood are the unintended consequences of air pollution interventions on indoor and outdoor air quality. This paper shows how the National Green Tribunal has targeted one source of air pollution in recommending waste-to-energy technologies that deprive waste pickers of their livelihoods. The pandemic-related lockdown provides an opportunity to assess the impacts of livelihood deprivation on fuel use. Using data collected from surveys of waste pickers, this paper shows that decreases in income are related to an increase in reliance on solid fuels. Therefore, we argue that air pollution interventions designed to control air pollution from poor waste management have the unintended consequence of increasing air pollution from a different source (biomass burning for cooking) that specifically impacts waste pickers by increasing their exposure to indoor air pollution, while also undermining the government's urban air pollution mitigation efforts overall. [ABSTRACT FROM AUTHOR]

The paper focuses on the automatic selection of the grouped explanatory variables in a high-dimensional model, when the model blue error is asymmetric. After introducing the model and notations, we define the adaptive group LASSO expectile estimator for which we prove the oracle properties: the sparsity and the asymptotic normality. Afterwards, the results are generalized by considering the asymmetric L q -norm loss function. The theoretical results are obtained in several cases with respect to the number of variable groups. This number can be fixed or dependent on the sample size n, with the possibility that it is of the same order as n. Note that these new estimators allow us to consider weaker assumptions on the data and on the model errors than the usual ones. Simulation study demonstrates the competitive performance of the proposed penalized expectile regression, especially when the samples size is close to the number of explanatory variables and model errors are asymmetrical. An application on air pollution data is considered. [ABSTRACT FROM AUTHOR]

Poor ambient air quality is one of today's greatest environmental health risks. However, unlike water, wildland fire, or wildlife, comparatively less human dimensions scholarship has focused on air resources. The papers in this special issue highlight how people across varying cultures, geographies, and identities create and relate to varying air quality conditions. In doing so, the issue challenges dominant perspectives of air pollution as a purely material entity and argues for the need to attend to the socio-cultural and political dimensions that define, create, or mitigate poor air quality. [ABSTRACT FROM AUTHOR]

Wood smoke pollution has emerged as a major public health issue in southern Chile. This paper endeavors to find evidence of environmental inequity by looking into the spatial associations between sociodemographic characteristics, exposures, and risk perception to air pollution. We integrate primary georeferenced survey data with estimates of excess outdoor exposure to wood smoke in Coyhaique, one of the most polluted cities in Latin America. Our findings reveal that certain social groups are disproportionately exposed to PM2.5. People of low-socioeconomic status, living in households with older adults and users of wood-burning stoves tend to spend more days per year with unhealthy air pollution levels. The results yield a modest but statistically significant relationship between PM2.5 levels and risk perception. Sociodemographic factors are also important predictors of air pollution risk perception. We discuss the implications in terms of environmental injustice patterns and public awareness campaigns. [ABSTRACT FROM AUTHOR]

Sensors and sensor systems for monitoring fine particles with aerodynamic diameters smaller than 2.5 µm can provide real-time feedback on indoor air quality and thus can help guide actions to manage indoor air pollutant concentrations. Standardized verification of the performance and accuracy of sensors and sensor systems is crucial for predicting the efficacy of such monitoring. A new ASTM International standard test method (ASTM D8405) was created for this need and is the most exacting laboratory protocol published to date for evaluating indoor air quality sensors and sensor systems measuring particles smaller than 2.5 µm in diameter. ASTM D8405 subjects sensors and sensor systems to five test phases: (1) an initial particle concentration ramp; (2) exposure to various temperature and humidity conditions; (3) exposure to interfering particles; (4) temperature cycling; and (5) a final particle concentration ramp to assess drift. This paper discusses the development of the standard test method, key aspects of the testing process, example evaluation results, and a comparison of this standard test method against peer evaluation protocols. [ABSTRACT FROM AUTHOR]

The U.S. EPA developed the Regional Haze Rule to address Section 7491 of the 1977 Clean Air Act Amendments to prevent any future and remedy any existing visibility impairment due to manmade air pollution at Federal Class I areas (CIAs). The rule addresses this national goal by requiring states to show they are making progress toward estimated natural conditions by 2064 for the 20% anthropogenically Most Impaired Days (MID). For the MID, days that have high haze contributions from wildfires and windblown dust tend to be excluded using haze contributions from Carbon and crustal material as surrogates. To show progress toward natural conditions in 2064, a Uniform Rate of Progress Glidepath is defined as a straight line from measured 2000–2004 IMPROVE MID Baseline to natural conditions in 2064. Photochemical modeling is used to project the observed IMPROVE 2014–2018 MID visibility to 2028 that is compared to the Glidepath at 2028 to determine whether the MID visibility at a CIA is on a path toward natural visibility conditions in 2064. This paper discusses an alternative approach for showing progress toward no manmade impairment by using modeling results to generate a U.S. Anthropogenic Emissions Rate of Progress (RoP). The CAMx photochemical grid model was run for a current year (representing 2014–2018), 2028 future year and a 2002 past year and source apportionment was used to isolate the contributions of U.S. anthropogenic emissions to PM concentrations and visibility extinction. A RoP slope line is drawn from the 2002 visibility extinction due to U.S. anthropogenic emissions to zero in 2064 and the CAMx 2028 visibility for U.S. anthropogenic emissions is compared with the RoP slope line at 2028 to determine whether visibility due to U.S. anthropogenic emissions is on a path toward no U.S. manmade impairment in 2064. Implications: The U.S. EPA Regional Haze Rule guidance to show progress toward no U.S. manmade visibility impairment at Class I Areas by 2064 backs into the U.S. manmade impairment contribution by using total atmospheric haze based on measured PM concentrations and subtracting uncertain estimates of routine natural and episodic (i.e. wildfires and windblown dust) natural conditions. The guidance also recommends accounting for visibility contributions due to international anthropogenic and prescribed fire emissions that are also uncertain. This paper presents an alternative approach that models the contributions of U.S. anthropogenic emissions to visibility for past, current and future years using source apportionment to show that U.S. anthropogenic emissions visibility impairment at Class I areas are on a path toward no contribution in 2064. Many U.S. anthropogenic emissions (e.g. power plants with continuous emissions monitoring systems) are better known and characterized than international, fire and natural emissions so the alternative approach should provide a better assessment of whether U.S. anthropogenic emissions are on a path toward no manmade impairment in 2064 than using trends in the measured visibility most impaired days that rely on uncertain estimates of haze due to wildfire, windblown dust, and international emissions and uncertain estimates of natural conditions in 2064. [ABSTRACT FROM AUTHOR]

"Residents Against Dirty Energy" (RADE) are a community-led energy activist group in Bristol city, UK. Since their inception, they have effectively lobbied the city council for the deployment of battery storage units in place of diesel generators in Lockleaze, north Bristol. As a result, Lockleaze now hosts battery storage facilities with 15MW of storage capacity able to store excess energy from the grid. Drawing on a focus group (n = 8) with local energy actors in Bristol and in-depth interviews (n = 2) with RADE, alongside document analysis of key secondary data sources, the paper uses three tenets of energy justice (distributional, recognition and procedural justice) to shed light on the role of local energy activism in shaping low-carbon energy infrastructures. The qualitative data reveals RADE's efforts to ensure that local communities are closely involved in energy decision-making, to ensure that the siting of new energy technologies does not burden marginalised communities. However, questions around distributionaleconomic benefits and ownership are secondary to RADE; their primary concern is with the improvement of local air quality and reducing harm to the local population and environment. These issues connect strongly to Bristol's divided landscape, underpinned by an unequal geography of socio-economic division and racial inequality. As such, the paper sees the further integration of "spatial justice" as a core tenet of energy justice as necessary to enhancing its explanatory power, concluding with a call for scholars and policymakers to further consider the visions and efforts of local and civil society energy activists in shaping just transitions. [ABSTRACT FROM AUTHOR]

Adapting to the situation of one principal versus several agents, the Relative Performance Evaluation (RPE) is an effective incentive tool to motivate subordinates. The Chinese central government has adopted RPE to combat intractable air pollution, which is the Urban Air Quality Ranking (UAQR) system. This study uses a series of econometric methods including regression discontinuity design to examine its effectiveness in environmental governance. The results show that (1) since the implementation of UAQR, the overall air quality of cities has improved; (2) air quality of the bottom 3 cities in the ranking will improve in the coming month compared with their counterparts; (3) while top 3 cities in the ranking do not experience such change in air quality. Therefore, this paper argues that the activating based RPE does not stimulate effective competition, whereas competency based RPE does. UAQR with credible incentive commitment can be a useful measure to motivate local authorities to strengthen air pollution reduction. In this study, the results of the empirical analysis enrich the theoretical framework of RPE, and an innovative theoretical framework is adopted to explain the UAQR system. However, as a top-down environmental monitoring system, such ranking institution could mainly eliminate centralized discharged pollutants. A sound judicial system is the fundamental guarantee for sustainable development. [ABSTRACT FROM AUTHOR]

The issue of environmental governance has received considerable attention. While extensive research focuses on the relationship between economic growth and environmental protection, this paper provides a different perspective by exploring the mechanisms affecting the relationship between land-based revenue and environmental performance. Based on the regression analyses of province-level data during 2000-2018 in China, the results show that: (1) land-based finance has a significantly positive impact on air pollution; (2) both central government policies and local residents' concerns incentivize local governments to improve environmental quality through land revenue; (3) regional differences exist regarding the impact of these two factors, probably due to various development stages and financial conditions; (4) local governments tend to increase expenditure on environmental protection by taking residents' concerns into consideration. This research contributes to understanding the driving forces behind the relationship between land finance and environmental performance, and it extends our knowledge of local governments' decision-making processes to accomplish multiple tasks. [ABSTRACT FROM AUTHOR]

Air pollution from residential wood heating poses a significant public health risk and is a primary cause of PM nonattainment in some areas of the United States. Those emissions also play a role in regional haze and climate change. While regulatory programs have focused on emissions reductions from large facilities, the residential heating sector has received limited attention. The failure to develop effective programs to address this emission source hampers the ability of state and local air quality programs to meet clean air goals. An updated New Source Performance Standard (NSPS) for Residential Wood Heaters was promulgated in 2015, which includes more stringent emissions standards for wood stoves and broadens its scope to regulate additional types of wood heating appliances. However, weaknesses in the test methods and programs used to certify compliance with the NSPS limits hamper the efficacy of those requirements. Current emissions certification tests measure stove performance under defined laboratory conditions that (1) do not adequately reflect operation and performance of appliances in homes, (2) are not sufficiently repeatable to allow for comparison of emissions of different appliances, and (3) allow manufacturers leeway to modify critical test fueling and operating parameters which can significantly impact performance outcomes. These foundational regulatory issues present substantial challenges to promoting the cleanest and most efficient wood heating systems. This paper provides an overview of the air quality and public health impacts of residential wood heating and discusses the weaknesses in the current emission certification approaches and work by the Northeast States for Coordinated Air Use Management (NESCAUM) and the New York State Energy Research and Development Authority to develop improved testing methods. Other articles in this issue discuss the development and testing of those methods in detail. Implications: Air pollution from residential wood heating poses a significant public health risk and is a primary cause of PM nonattainment in some areas of the United States. Those emissions also play a role in regional haze and climate change. While regulatory programs have focused on emissions reductions from large facilities, the residential heating sector has received limited attention. The failure to develop effective programs to address this emission source hampers the ability of state and local air quality programs to meet clean air goals. This paper provides an overview of the issue. [ABSTRACT FROM AUTHOR]

The paper analyzes the prerequisites for a regulatory-driven transition toward radically lower air and water pollution in industry. This is achieved in the empirical context of the Swedish mining and metals industry, and by investigating the environmental licensing processes during two regulatory systems. The paper derives an analytical framework that explores under what circumstances such licensing processes can result in radical emissions reductions without seriously jeopardizing the competitiveness of the industry. Archived material covering six environmental licensing processes, three during each system, is used to illustrate the various design and implementation issues. The results suggest that regulatory-driven green transitions benefit from trust-based bargaining procedures in which companies are involved in repeated interactions with regulatory authorities, and which extended probation periods permit tests of novel abatement technologies (including innovation). The findings also illustrate the importance of abstaining from simplified normative notions about policy instrument choice (e.g. taxes versus standards). [ABSTRACT FROM AUTHOR]

Citizen science is advocated as a response to a broad range of contemporary societal and ecological challenges. However, there are widely varying models of citizen science which may either challenge or reinforce existing knowledge paradigms and associated power dynamics. This paper explores different approaches to citizen science in the context of air quality monitoring in terms of their implications for environmental justice. This is achieved through a case study of air quality management in Dublin which focuses on the role of citizen science in this context. The evidence shows that the dominant interpretation of citizen science in Dublin is that it provides a means to promote awareness and behaviour change rather than to generate knowledge and inform new regulations or policies. This is linked to an overall context of technocratic governance and the exclusion of non-experts from decision-making. It is further closely linked to neoliberal governance imperatives to individualise responsibility and promote market-based solutions to environmental challenges. Last, the evidence highlights that this model of citizen science risks compounding inequalities by transferring responsibility and blame for air pollution to those who have limited resources to address it. Overall, the paper highlights the need for critical analysis of the implications of citizen science in different instances and for alternative models of citizen science whereby communities would contribute to setting objectives and determining how their data is used. [ABSTRACT FROM AUTHOR]

To prevent air pollution and achieve air quality regulations, it is essential to develop analytical techniques that can determine the concentration of metals in aerosol particles, both in the gas phase and after collection onto filters. Total reflection X-ray fluorescence spectroscopy (TXRF) and laser-induced breakdown spectroscopy (LIBS) are emerging as complementary techniques for determining the elemental composition of aerosol particles. The accuracy of their results relies on calibration methods based on aerosol and multi-element filters representative of the on-line measurement conditions and particulate collection for off-line measurement, respectively. In this paper we propose a novel methodology for characterizing nebulization generated aerosol particles dispersion and deposition by means of TXRF to assess the use of an aerosol generator to produce calibration samples for LIBS and TXRF analysis. Particles concentration and size distribution of the aerosol produced by nebulizing a Cu salt aqueous solution are measured inside a glove box modifying the production parameters and collecting the corresponding particulate deposited on reflectors. The most stable conditions are observed at average flow rate and selected for studying the aerosol spatial distribution. The Cu mass collected on reflectors positioned at a fixed distance and radial geometry with respect to the nozzle exit is measured by TXRF and increases linearly with time. Results suggest that this experimental configuration could be used to realize calibration samples for TXRF analysis representative of particulate deposition. The use of these aerosols as LIBS calibration samples could lead to significant errors due to the observed flow asymmetry. Copyright © 2022 American Association for Aerosol Research [ABSTRACT FROM AUTHOR]

In this paper, we propose a novel group variance inflation factor (VIF) regression model for tackling large data sets where data follows a grouped structure. Unlike classical penalized methods, this approach can perform group variable selection in a sparse model, which is quite different from the classical penalized methods. We further adapt the proposed method associated with a two-stage procedure for detecting multiple change-point in linear models. We carry out extensive simulation studies to show that the proposed group variable selection and change-point detection methods are stable and efficient. Finally, we provide two real data examples, including a body fat data set and an air pollution data set, to illustrate the performance of our algorithms in group selection and change-point detection. [ABSTRACT FROM AUTHOR]

California's Office of Environmental Health Hazard Assessment has updated the comprehensive age-specific model of lead metabolism in humans published by Richard W. Leggett in 1993. The updated model, called Leggett+, was introduced in a peer-reviewed report in 2013. The Leggett + model simulates the relationship between blood lead and exposure in the workplace. Leggett + includes a workplace exposure model comprising respiratory tract intake (workplace lead inhaled by a worker) and uptake (lead absorbed into the blood from the respiratory tract plus uptake from ambient air and diet). The latter is calculated as intake times an inhalation transfer coefficient plus background uptake. An adjusted adult systemic model describes the metabolism of the absorbed lead. This paper provides details about the workplace exposure and uptake elements of Leggett+, an updated approach to calibrating an inhalation transfer coefficient, confirmation of the model's performance in predicting blood lead levels from workplace studies, and predictions of blood lead levels from simulated exposures to workplace airborne lead over a working lifetime. Blood lead relative to airborne lead concentrations in a standard workplace scenario predicted by Leggett + was similar to corresponding relationships from four published workplace studies. Leggett + predictions displayed a good fit to regression equations when other key factors were considered such as pre-employment blood lead and ongoing background intake of lead, workplace air concentration, lead aerosol characteristics, and worker activity levels. The comprehensive Leggett + model can simulate plausible workplace air–blood lead relationships from a broad range of worker exposures. The inhalation transfer coefficient of 0.30, derived from empirical data described in the 2013 report has been reexamined. The original estimate continues to represent a plausible mid-point for a coefficient derived from an expanded range of theoretical particle size distributions deposited in the upper and lower regions of the respiratory tract considering intake during sedentary and outdoor activity breathing scenarios. This coefficient is slightly lower than the value of 0.35 estimated for unknown forms of lead by Leggett in 1993. [ABSTRACT FROM AUTHOR]

Atmospheric polycyclic aromatic hydrocarbons (PAHs) are associated with adverse health effects in exposed populations. Understanding PAH pollution in ambient air and its adverse impacts is essential for developing effective actions for combating air pollution. This review paper summarised and discussed the findings of research work that determined the concentrations, distribution sequence, and health risk exposure levels of atmospheric PAHs in cities worldwide. It also gave an overview of the sources and the methodology for appraising the health risk of exposure to atmospheric PAHs. Eighty-five articles published in peer-reviewed journals from 2010 to 2023 were identified in academic research databases, with 55 reporting on sources and distribution of atmospheric PAHs, while 30 evaluated the health risk of exposure to PAHs in ambient air. The narrative review approach was employed to critically analyse and produce descriptive summaries of distribution patterns and health risk exposure levels of atmospheric PAHs in a tabular form. The review showed that the total PAH concentration in urban areas was about eight times greater than in rural environments and emanated from diverse sources. However, vehicle exhaust and industrial emissions were the primary sources of atmospheric PAHs. The distribution sequence of PAHs in particulate and gas phases was HMW>MMW>LMW PAHs and LMW>MMW>HMW PAHs, respectively. Chronic exposure to PAHs in the environment increased the risk of asthma, cardiovascular disease, and lung cancer. Adoption of stricter emission standards, cleaner energy sources, and more efficient industrial technology will aid in the reduction of particulate PAH pollution and its negative health consequences in urban areas. [ABSTRACT FROM AUTHOR]

In recent years, our world has experienced significant disruptions due to the COVID-19 pandemic, and Russia's 2022 invasion of Ukraine, impacting human activities and the global environment. This paper explored air quality changes in Ukraine due to COVID-19, and Russia's invasion of Ukraine using on-demand with a what-you-see-is-what-you-get approach. During the COVID-19 pandemic, strict quarantine policies in Ukraine led to a 2% reduction in tropospheric NO2 concentration before the lockdown and 4% during the lockdown period. Cities like Kyiv, Donetsk, and Dnipro exhibited reductions of 5%, 11%, and 16%, respectively. Total SO2 column concentration decreased by 6% before the lockdown and 2.5% during the lockdown period, except in high population density areas. Kyiv showed the highest reduction of 17% in SO2 concentration, while Donetsk and Dnipro exhibited an 11% reduction. However, during the Russian invasion, there was a significant increase in tropospheric NO2 concentration in heavily destroyed Kharkiv while most eastern regions experienced a reduction. The total SO2 column was 48% higher before the war but reduced throughout the country after the war, except for in Kyiv and a few central regions. These findings can contribute to analyzing air pollution and building digital twin simulations for future reconstruction scenarios. [ABSTRACT FROM AUTHOR]

Coal combustion is the primary source of air pollution in China, especially the heavy metals (HMs) concentrated in the submicron particles. This paper discusses the enhancement of HMs absorption efficiencies during coal combustion experiments. By adding the modified Ca-based sorbents, the orthogonal design was used in this experiment. Combining with the analysis of variance and capturing rate of HMs, the optimal combination was arrived at. BP neural network model was established and trained using orthogonal capturing tests data to reach the best compositions. Confirmatory trial was conducted, thus the BP neural network model can be used to solve complex nonlinear optimization problems. [ABSTRACT FROM AUTHOR]

This paper reports a study on the statistics for particulate matter pollution (PM2.5) and the COVID-19 lockdown in the Kathmandu valley. The PM2.5 decreased during the COVID-19 pandemic lockdown periods 2020 compared to the average value of the previous three years (2017, 2018, and 2019). Further, analysis of active fire and air mass trajectory for April and May in 2019 and 2020 shows that the particulate matter trend associated with Kathmandu is not directly influenced by the long-range transport of wind carrying aerosols from the active fire regions. Statistical tests indicate a reduction of particulate matter pollution during the period. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has had many impacts on the environment worldwide. This paper examines the effects of this pandemic on the air pollution in the four major cities (Delhi, Kolkata, Mumbai, and Hyderabad) of India. The research reveals the impact on the levels of the various pollutants and the Air Quality Index. This paper contrasts the four phases' behaviour during the nationwide lockdown, imposed to control the pandemic, and reports the behaviour of air pollutants and the air quality index compared to 2019. [ABSTRACT FROM AUTHOR]

In recent years, recycling of municipal solid waste (MSW) has been recognized as one of the most efficient methods of waste management in terms of environmental benefits. This study investigates the energy savings and other environmental benefits of recycling of dry MSW collected in Shiraz, Iran (2018). The impact of different recycling rates (current = 15%, desirable = 50%, ideal = 80%) on environmental benefits and energy savings were assessed. The annual quantity of recycled components were defined as glass (735 tons), plastic carrier bags (555 tons), cardboard (3,874 tons), paper (3,806 tons), disposable plastic containers (287 tons), other types of metals (785 tons), disposable metallic containers (aluminum) (171 tons), other types of plastics (812 tons) and polyethylene terephthalate (PET) (887 tons). The results confirmed that recycling of paper and glass in three different scenarios resulted in a reduction of 1.01, 2.14, and 3.43 million tons of air pollutant emissions, respectively. By improving the recycling rates from 15 to 80%, overall energy savings can improve by between a factor of 3.5 to 5.5. Also, a reduction of approximately 2–3.5% in air pollutant emissions can be achieved by upgrading the current recycling program (15% recycling rate) to favorable and ideal conditions. Implications: In recent years, recycling of municipal solid waste (MSW) has been recognized as one of the most efficient methods of waste management in terms of environmental benefits. This study investigates the energy savings and other environmental benefits of recycling of dry MSW collected in Shiraz, Iran (2018). According to available data, there has been little effort for recycling in developing countries, and waste landfilling is recognized as the most favorable option in MSW management. The aim of this study was to characterize MSW components in Shiraz, Iran, and to quantify the environmental benefits and energy savings as result of paper, glass, and aluminum recycling. This work is novel in that there are no reports to our knowledge of the environmental benefits and energy savings resulting from different recycling scenarios including current (15%), desirable (50%), and ideal (80%) recycling for aluminum, paper, and glass. The results of this work have broad implications both for other regions owing to the pervasiveness of recycling facilities and also for developing countries that can strive towards the infrastructure needed to reach improved recycling scenarios. [ABSTRACT FROM AUTHOR]

Atmospheric pollution refers to the presence of substances in the air such as particulate matter (PM) which has a negative impact in population ́s health exposed to it. This makes it a topic of current interest. Since the Metropolitan Zone of the Valley of Mexico's geographic characteristics do not allow proper ventilation and due to its population's density a significant quantity of poor air quality events are registered. This paper proposes a methodology to improve the forecasting of PM10 and PM2.5, in largely populated areas, using a recurrent long-term/short-term memory (LSTM) network optimized by the Ant Colony Optimization (ACO) algorithm. The experimental results show an improved performance in reducing the error by around 13.00% in RMSE and 14.82% in MAE using as reference the averaged results obtained by the LSTM deep neural network. Overall, the current study proposes a methodology to be studied in the future to improve different forecasting techniques in real-life applications where there is no need to respond in real time. Implications: This contribution presents a methodology to deal with the highly non-linear modeling of airborne particulate matter (both PM10 and PM2.5). Most linear approaches to this modeling problem are often not accurate enough when dealing with this type of data. In addition, most machine learning methods require extensive training or have problems when dealing with noise embedded in the time-series data. The proposed methodology deals with this data in three stages: preprocessing, modeling, and optimization. In the preprocessing stage, data is acquired and imputed any missing data. This ensures that the modeling process is robust even when there are errors in the acquired data and is invalid, or the data is missing. In the modeling stage, a recurrent deep neural network called LSTM (Long-Short Term Memory) is used, which shows that regardless of the monitoring station and the geographical characteristics of the site, the resulting model shows accurate and robust results. Furthermore, the optimization stage deals with enhancing the capability of the data modeling by using swarm intelligence algorithms (Ant Colony Optimization, in this case). The results presented in this study were compared with other works that presented traditional algorithms, such as multi-layer perceptron, traditional deep neural networks, and common spatiotemporal models, which show the feasibility of the methodology presented in this contribution. Lastly, the advantages of using this methodology are highlighted. [ABSTRACT FROM AUTHOR]

This review paper provides a perspective on residue generation, reasons for on-site burning of residue, its ill effects on soil properties, environment, soil biota, challenges faced by the farmers in managing a huge quantity of residue and various schemes, policies, and punishments undertaken by the government to curb the problem of on-site residue burning. Several studies show that crop residue burning in the field has a negative impact on soil organic carbon, soil fertility, soil microbes, and environment and also hinders the long-term sustainability of crop production. Crop residue is a good source of carbon, nitrogen, phosphorus, potassium, and sulfur; on burning, these cause the loss of nutrients as CO, CO2, NO, particulate matter, and smoke, which are lost into the atmosphere, thereby creating the problem of air pollution and global warming, which will also pose threat to human health. [ABSTRACT FROM AUTHOR]

Green plants can effectively retain atmospheric particle pollution and purify the air. As an important part of the campus ecosystem, they have a significant effect on absorbing atmospheric pollutants and improving the quality of the campus air environment. Six common greening plants were selected as the object in Xiangnan University. The dust retention capacity of plant leaves, leaf micro-structure, and leaf contact angle were measured. The results show that the highest amounts of dust removed by Osmanthus fragrans Lour was 3.451 g/m2, and the least amounts of dust removed by Magnolia denudata Desr. was 1.005 g/m2, and the maximum is 4.148 times of the minimum. The micro-structure of the plant leaf surface affects the amount of dust retention. The plant dust retention capacity with gully of the leaf surface and fluff, stomata, and sawtooth structure is relatively strong; The plant dust retention capacity with smooth, wax layer, leathery, and gully is relatively weak. The leaf contact area of a plant is related to its dust retention ability, that is, when the measured leaf contact angle is <90°, the leaf dust retention ability of the plant is strong. When the blade contact angle is >90°, the dust retention capacity is weak. Many studies have found that green plants can effectively retain atmospheric particle pollution and purify the air. As an important part of the campus ecosystem, few people specially study the campus ecosystem. Many scholars focus on the research on urban street trees and different districts of the city. The object of this study is more in-depth and targeted. Through the analysis of the difference of dust retention ability between common plants in campus, this paper compares and analyzes the influencing factors of the difference of dust retention ability among plants, which is not only related to the external environment but also closely related to the micro-structure characteristics of plant leaves. The research on the dust retention ability of different plants will help to better control dust and atmospheric environmental pollution, improve air quality, and select plants with strong dust retention ability as green plants on campus, which will play an important role in reducing dust pollution on campus. [ABSTRACT FROM AUTHOR]

The COVID-19 pandemic has affected lifestyles everywhere, changing urban traffic circulation worldwide. This paper focuses on the impact of the pandemic on air pollution from mobile sources in a Latin American medium-size city: Bahía Blanca (Argentina). Vehicle flow and corresponding emissions were evaluated before (January and March 2020) and after (June and November 2020) the lockdown. Vehicular traffic flows were measured and their segmentations were calculated. Emissions dispersion was modelled by employing R-Line, through the use of AERMOD. A decrease was observed not only in vehicular flow (~23%), but also in pollutant and greenhouse gas concentrations (~70%), in line with other research. Changes in mobility habits were observed, which were reflected by the different proportion of the vehicle-fleet segmentation, with a significant drop in the buses (~66%) together with the appearance of a bicycle peak (~53%), which is unusual for the city. [ABSTRACT FROM AUTHOR]

This study comprehensively analyzed air pollution in Chengdu (CD), a megacity in southwest China, evaluated the Variation Characteristics of air quality during 2015–2018, and conducted Random Forest classification of air pollution data of 2017. The classification results showed three pollution periods: severe (December, January and February), ozone (May‒August), and slight (March and November). These features were combined with potential source contribution function (PSCF), concentration weighted trajectory (CWT) and backward trajectory model (HYSPLIT) for simulating spatio-temporal trajectory of air polluted during each pollution periods. The results show that PM2.5 mainly comes from CD and surrounding cities, and some may be from India, Myanmar and Chongqing; PM10 mainly comes from CD and surrounding cities and some may be from India and Myanmar; NO2 mainly comes from CD and surrounding cities and cities and Some of the pollution may come from the input of India, Myanmar, Chongqing and Inner Mongolia; O3 mainly comes from the urban agglomeration of Sichuan Basin and some areas from Chongqing, Sichuan Liangshan and Yunnan Guizhou. Combined with the meteorological data of temperature, relative humidity and wind speed, aerosol optical depth, planetary boundary layer height and thermal anomaly data, the Monthly, daily and hourly spatio-temporal characteristics and the possible occurred cause of the main air pollution during each pollution period in CD were revealed detail. The research in this paper is critical for pollution control and prevention and provides a scientific basis for studying the spatio-temporal characteristics and sources of pollution in megacities in terrain such as basins and mountains. Implications: Air pollution has a significant impact on human and ecological health. In 2013, Chengdu was one of the five cities with the most serious PM2.5 pollution in the world. In the previous study of air pollution in Chengdu, it was only for a short period of pollution. It is impossible to fully understand the spatio-temporal trajectory and cause of air pollution. Chengdu is surrounded by mountains, and the meteorological conditions have been stagnant for a long time. The research on the spatio-temporal evolution of the main air pollution trajectories in each pollution period in Chengdu is particularly important. Quantifying the pollution trajectory and air pollution concentration is helpful to fully understand the air quality in Chengdu. The comprehensive analysis of multi-source data such as air pollution and meteorology has focused on strengthening the in-depth research on the transmission law of air pollution, the spatio-temporal change trend of air pollution, the sources of air pollution and the causes of air pollution, so as to help people fully understand the sources and causes of pollution in Chengdu. Aiming at the trajectory law, causes and occurrence time of air pollution, it is conducive for the government to formulate corresponding policies, carry out regional emission reduction and joint prevention and control, improve air quality and minimize the harm of air pollution to the public. [ABSTRACT FROM AUTHOR]

Air pollution and its limits are regulated by the environmental protection agency of an individual country according to their National Ambient Air Quality Standards (NAAQS). Particulate matter (e.g., TSP, PM10, and PM2.5) is one of the important criteria pollutants of NAAQS. Their measurement methods are specified in NAAQS, and detailed technical descriptions are given in standards. This review focuses on the sampling and analysis techniques and methods in the context of PM samplers' design mentioned in countries specific PM measuring standards (e.g., EPA Part 50, CEN 12341, IS 5182(23), etc.) and their comparison wherever is necessary. It discusses, different designs of PM samplers mentioned in standards and its important components, e.g., size fractionators cutoff efficiency, PM sampler head design, flow measurement, and calibration, and also addresses the important issues that are the limitation of present standards. Our review reveals that most of the country-specific standards show common practice in measuring PM2.5 using WINS impactor and VSCC cyclone as mentioned in EPA Part 50, except European Union (EU) standards, which has different design and parameters. For PM10 measurement, sampler design is different in EU and Indian standards than that of U.S. EPA and other countries' standards, which is discussed in length here. All standards lack in pointing some inherent problems like change in D50 cutoff of size fractionator of sampler under a high particle mass loading condition, which is common in countries like China and India. Other important issues where most of the standards lack include PM head design and specification, a key component of PM sampler on which the mass measurement results are largely dependent. Implications: The review paper discusses the air quality standards compliances of different countries and their comparisons. It focuses on the sampling and analysis techniques in context of PM samplers' design mentioned in countries specific PM measuring standards, and also addresses the important issues that are not mentioned in standards. Therefore, the discussions and findings of the review may be very useful while revising the existing air quality standards of different countries and to fill the research gap in this domain. Further, we have discussed several technical issues described in standards related to PM sampling which may be very helpful for PM sampler designing or modification in current designs as per the prevailing ambient conditions of a country. [ABSTRACT FROM AUTHOR]

Enhancing the Nationally Determined Contributions (NDCs) is an important exercise to achieve the long-term goals of the Paris Agreement. The Paris Agreement also recognizes that support to developing countries in this regard will help them to aim for higher climate ambition. The role of international support programmes in the NDC enhancement process is crucial but is not often covered in scientific research. Consequently, the factors driving a country's decision to apply for NDC-related assistance have also not yet been fully explored. Acknowledging the research gap, this paper framed and tested multiple hypotheses to evaluate the impact of potential factors on the likelihood of a country applying for assistance to enhance its NDCs. For this, a logistic regression method was employed. Data from the two initiatives coordinating the technical and financial assistance worldwide, namely the Climate Action Enhancement Package (CAEP) and Climate Promise, were reviewed for this purpose. The CAEP program is financially supported by Denmark, Germany, Netherlands, Norway, Sweden and the UK. This study identifies the level of socio-economic development and the population's exposure to air pollution as key factors which influence the likelihood of applying for assistance under CAEP and Climate Promise in developing countries. Further, the presence of democratic aspects in the form of governance may also influence this choice. Finally, this study discusses the results and associated policy implications for countries receiving assistance to enhance their NDCs. Developing countries with relatively low socio-economic development are more likely to apply for assistance to enhance their NDCs. The assistance is designed to help them to build capacities to develop and implement future climate policies. Air pollution and climate change issues are interconnected. Exposure to air pollution is a potential indicator that can influence the NDC enhancement process in developing countries. The assistance for enhancing NDCs will lead to NDC targets that are well-informed and are aligned with national and sub-national development priorities with realistic prospects of implementation. Climate vulnerability and net trade do not influence the decision-making process to apply for NDC enhancement assistance. [ABSTRACT FROM AUTHOR]

Governments all over the world have had to implement various policy measures in order to curb the spread of COVID-19, impacting many people's lives and livelihoods. Combinations of measures targeting the transportation sector and other aspects of social life have been implemented with varying degrees of success in different countries. This paper proposes a classification of COVID-19 measures aimed at passenger mobility. We distinguish the categories "avoidance of travel", "modal shift" and "improvement of quality". Per category, we distinguish different types of measures and effects (social, economic and environmental). Next, we review the literature on COVID-19 measures for passenger mobility, after which we discuss the policy relevance of our findings and propose a research agenda. We conclude that broad or integral assessments of measures on all socially relevant effects are rare. Also, few studies exist to determine the effects of individual measures and deal with combinations of measures instead. Studies on social or economic effects focus on partial direct effects (e.g. turnover of the transport sector, effect of mobility measures on commuter traffic) and do not elaborate on indirect effects (e.g. changes in household expenditure, stress levels). Finally, there is a greater focus in the literature on intermediary health indicators (e.g. travel behaviour) but less on the actual spread of COVID-19 or indeed on other indirect health effects of measures (e.g. due to air pollution, more exercise, etc). [ABSTRACT FROM AUTHOR]

The paper aims to quantify the changes in the pollutants level in the ambient air of Madhya Pradesh during COVID-19 induced 21 days lockdown. The data of 16 continuous ambient air quality monitoring stations (CAAQMS) for six pollutants, namely PM2.5, PM10, SO2, NOx, CO, and Ozone for pre-lockdown (1–21 March 2020) and lockdown (25 March-14 April 2020) period was compiled and appropriate statistical analysis was done. The result showed a reduction of 13%, 20%, 37%, 39% and 25% in the ambient air level of PM2.5, PM10, SO2, NOx and CO, respectively, during the lockdown. No such declining trend was observed in the ambient air ozone level. Ambient air ozone level changed between −22 and +30% compared to pre-lockdown concentrations. The mean ambient air ozone concentration was reduced at the residential/commercial stations (−5%), but was increased at the industrial stations (+19%) concentration. [ABSTRACT FROM AUTHOR]

To reduce the pollution from the atmosphere or polluted cities like the capital city Delhi of India, use of artificial rain is a solution. In this paper, we have proposed and analyzed a nonlinear mathematical model to reduce the pollution level by rain making. In the proposed model five variables are considered, namely; (i) number density of water vapor, (ii) number density of cloud drops, (iii) number density of raindrops, (iv) cumulative concentration of aerosols, and (v) concentration of pollutant particles suspended in the region of consideration. The effect of environmental fluctuations has been studied with the help of Lyapunov functionals. The model is analyzed in the presence of white noise and proved that if rain persists, the pollutants can be totally washed out. It has been observed that the environmental disturbances are not much favorable in such experiments as the presence of environmental disturbance may destabilize the system. It is found that to remove pollutants completely, it is necessary to prevent the formation of pollutants. The simulation is performed to support the analytical findings. [ABSTRACT FROM AUTHOR]

While many national and local governments in the world are placing their bets on smart city development in countering challenges such as climate change, air pollution, and congestion, few know exactly how to develop them in practice. A high and rising number of publications has appeared addressing the concept of "smart city," but not many address its implementation. This paper aims at a conceptual understanding of the smart city by describing its various facets and using them to develop an Input-Output model helping policymakers and analysts make informed design choices. Using this model allows them to further their conceptual understanding of smart cities, envisage design choices they will face during planning and implementation, and help them to understand the impact of these choices. The model is illustrated by introducing the case of "Smart Dubai." Overall, this paper provides enhanced understanding of smart city development processes. This can be used in decision-making processes. [ABSTRACT FROM AUTHOR]

Compositional data frequently arise when data refer to components which are proportions or fractions of a whole. Within the log-ratio approach, the analysis of compositional data can be conducted in terms of log-ratio transformations of components. These transformations make it possible to overcome the problem of the constant-sum constraint, making standard statistical methods applicable. In the present work, the log-ratio approach based on orthogonal log-ratio coordinates is adopted to show how it can lead to considerable improvements in the interpretation of the results of regression modeling with compositional data, both as explanatory or response variables. In order to demonstrate its practical usefulness, the methodology presented in this paper is applied to the analysis of air pollution produced by vehicles traveling through road intersections, with a specific focus on the effect of the type of traffic control (traffic signal vs. roundabout) on CO2 emissions. [ABSTRACT FROM AUTHOR]

Seoul, the capital city of Korea with over 10 million residents, has been experiencing serious air pollution problems. Previous studies on source apportionment of PM2.5 in Seoul are based on measurements of chemical compositions of PM2.5 from a single monitoring site. In this paper, we analyse PM2.5 concentration data collected from multiple sites in 24 districts of Seoul and estimate regional source profiles using Bayesian multivariate receptor model. The regional source profiles provide information for the identification of major PM2.5 sources as well as the regions relatively more seriously affected by each source than other regions. These regional characteristics relevant to PM2.5 can help establish effective, customised, region-specific PM2.5 control strategies for each region rather than general strategies that apply to every region of Seoul. [ABSTRACT FROM AUTHOR]

Total emissions from all sources need to be accurately quantified in an emission inventory in order for a basin to develop their air pollution management plan. The best approach is to measure both the real-world emissions and activity for a source; however, often only emissions are measured and activity is estimated from historical factors. This report focuses on harbor craft and presents data showing that using measured emissions and historical factors for activity will lead to inaccurate emission contributions. In this research, real-world activity data were collected from the engine control module (ECM) and from a surrogate method that relied on exhaust temperature. Measured real-world activity values from 10 harbor craft were compared with historical values found in the certification cycle. The vessels included four tugboats, three pilot boats, two police boats, and one supply vessel. The results showed the activity values used in the certification cycle did not reflect the real-world activity of the 10 harbor craft vessels. On average, real-world NOx emissions were only 46% of the NOx emissions estimated by ISO 8178-E3 weighting factor. In contrast, inclusion of significantly lower load factors leads to 31% higher in-use NOx emission factors on average. CARB/EPA load factor ranges from 0.45 to 0.51 while in-use load factor ranged from 0.14 to 0.44. From this finding, researchers are cautioned about accepting the activity values in a certification test cycle, like ISO 8178 E3, and instead should measure real world activity data. This change would improve the accuracy of the emission contribution from harbor craft to the local inventory. Implications: Real-world measurements of activity and emissions are the best way to get an accurate emission contribution to emission inventory. This paper reports on the differences between the use of the traditional certification cycle and real-world activity of harbor craft. Engine control module (ECM) and exhaust temperature data from 10 harbor crafts with different types of operation were used to compare real-world activity data to certification cycle. [ABSTRACT FROM AUTHOR]

Implementation outcomes of the Ambient Air Quality Directive (AAQD) (2008/50/EC)) are weak across European Union (EU) member states. In the UK, Local Authorities (LAs) must work toward reducing air pollution, however, means of assessing the extent and effectiveness of their contribution are limited. This paper develops a framework to evaluate policies implemented by UK LAs to address air pollution and applies it to Air Quality Action Plans (AQAP) of five cities. It looks at how, and the extent to which, LA air quality policies align with AAQD requirements, thus advancing empirical and academic knowledge on implementation literature surrounding multi-level governance, specifically the policy disconnect between the AAQD and UK Local Air Quality Management (LAQM). The application of the framework shows how LAs can better integrate AQAPs into their LAQM plans to assess, develop, improve and implement their air quality policies on the ground. [ABSTRACT FROM AUTHOR]

The implementation of chemical filtration in air-conditioning systems in archive and library repositories has become standard practice for heritage institutions in many countries. This practice is codified in official standards with general reference to a substantial body of scientific publications on the effects of air pollutants on paper materials. In this paper we report the application of a well-established decision analysis approach elaborating an integral cost-benefit perspective to provide decision support to four European national heritage institutions confronted with dilemmas in connection to chemical air filtration. Available scientific evidence for air pollution induced damage of paper material is reviewed and weighed against financial and environmental costs of air pollution control. Exposure of paper to both indoor and outdoor generated air pollutants at typical concentration levels observed within storage areas is expected to cause minimal to no additional yellowing and embrittlement, while the costs of chemical air filtration are significant. From a cost-benefit perspective the use of chemical air filtration in typical library and archive repositories is therefore discouraged. [ABSTRACT FROM PUBLISHER]

This paper presents the factors that influence firewood use among electrified Bapedi households in Senwabarwana Villages. The study follows explanatory and exploratory methods of data analysis, through survey (structured interviews) and meta-analysis. In-depth content analysis was followed to establish trends and identify factors that influence the use of firewood among electrified households globally and in the current study area. The results confirm that firewood is still the most common energy resource used for cooking, as well as water and space heating in many developing countries. Major drivers of firewood use are household income, educational status of breadwinners, family size, and place of residence, fuel affordability and accessibility. One of the key findings of this paper is that firewood use is also a psychological and behavioural issue as well as an economic one. There are indigenous and socio-cultural perceptions attached to the use of different energy sources. It is for these reasons, among others, that most communities do not stop using firewood even when they have access to electricity. However, the results reveal a shift from dependence on firewood to other energy sources as household income and educational levels improve. The latter is primarily a convenient factor of energy selection. In conclusion, the current study concludes that firewood use is primarily driven by convenience. The more convenient the source of energy, the more attractive it becomes to different households. [ABSTRACT FROM AUTHOR]

Climate change, urbanisation and demographic change affect urban areas and pose a range of health-related challenges to urban residents, including heat waves, drought periods, air pollution and densification processes. Urban green spaces provide ecosystem services that can help to mitigate the effects of these challenges. Urban green spaces such as parks, urban gardens and street trees regulate the microclimate and buffer noise as well as a variety of air pollutants. Parks promote physical activity, relaxation and social interaction. The potential to provide these services might be limited during extreme weather events such as heat waves and drought periods. With this experience-based perspective paper, we introduce an interdisciplinary project that consists of multi-method field campaigns to assess the potential of urban parks to provide regulating and recreational ecosystem services in the context of the 2018 and 2019 heat and drought periods in Germany. We highlight that multi-method field campaigns that combine sensor-based environmental measurements with social science approaches, including visitor observations, counts, and questionnaire surveys, are highly useful when urbanisation and climate change-related challenges must be effectively addressed in the context of the complex socio-ecological systems of a city. Based on our hands-on experiences, we provide recommendations for local urban green space planning and outline prospects for future research. [ABSTRACT FROM AUTHOR]