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We evaluated and compared the physiological and morphological response to pollution of two epiphytic lichen species, the foliose lichen Flavopunctelia praesignis and the fruticose lichen Usnea ceratina. Lichen samples were collected at remote areas and transplanted at different distances and directions from a paper industry in Morelia (Michoacán, Mexico). Lichen transplants were exposed for 4 months (1) around the industrial area and (2) in their native habitats (control sites). Changes of total chlorophyll content between samples before and after exposure, and morphological damage in the lichen thalli were investigated. Lichens showed species-specific responses. Flavopunctelia praesignis increased in total chlorophyll content after exposure around the industrial area and in control site. This suggests that total chlorophyll changes by a seasonal effect than pollution effect. On the other hand, chlorophyll content of U. ceratina did not change significantly after exposure. Bleaching, changes in color, deformations, and necrosis of lichen thalli were better visible in U. ceratina near the paper industry. We conclude that U. ceratina is a more pollution-sensitive species than F. praesignis. Morphological damage in the lichen thalli would be a suitable indicator for monitoring early biological effects of air pollution caused by the paper industry. [ABSTRACT FROM AUTHOR]

Objectives Paper dust has previously been linked to adverse health effects. However, a comprehensive dataset of paper dust exposures does not appear to have been published previously. Our study was intended to address this need by describing a large dataset of measurements made in Swedish soft tissue paper mills. Methods We compiled personal and area total dust exposure measurements collected from a range of operations by our research staff at four soft tissue paper mills in Sweden. We also compiled measurements made by the occupational health staff at each mill and the Swedish Work Environment Authority. We analyzed these measurements to describe patterns and trends in exposures and used mixed-effects regression models to identify measurement characteristics that predicted exposure levels. Results We compiled 1578 measurements from 1971 to 2009, of which 1026 (65%) were personal samples. Statistically significant differences were found between measurements made by research, mill, and Swedish Work Environment Authority staff, as well as between personal and area measurements. The measurement data suggest that, beginning in the 1980s, exposures declined at three of the four mills, but that overexposures were still common at the end of the period. Papermaking and converting operations had the highest observed dust exposures. One mill had significantly lower exposures than the others. Type of measurement (personal versus area) and source of measurement (research staff, company, or regulatory agency) were not significant predictors of measured total dust exposure after controlling for mill, operation, and time. Conclusions Our analysis of measured paper dust exposures may be useful for historical and contemporary exposure assessment in our own and other epidemiological studies. We have identified specific characteristics (i.e. papermaking operations and mill) and time trends that are important data features to consider, and documented continuing overexposure situations. Our results highlight the ongoing need for application of exposure controls to reduce paper dust exposures in the soft tissue paper industry. [ABSTRACT FROM AUTHOR]

Abstract To reduce pollution emissions and achieve a cleaner production in paper industry, it is essential to understand the inner links between concentrations of gaseous pollutants, types of final products and production techniques. In this study, the concentrations of four potential gaseous pollutants, total volatile organic compounds (TVOC), formaldehyde (HCHO), hydrogen sulfide (H 2 S), and hydrocarbon compounds (C x H y), in the ambient air on thirty sampling points of five pulp and paper mills were detected and analyzed. The results were summarized with respect to the following aspects: (1) Levels of four gaseous pollutants on all the sampling points in five mills. It was obvious that the situation of gaseous pollution from pulp mill was much more serious than those from paper mills. (2) Gaseous pollutant distinctions due to different production processes. The levels of gaseous pollutants from five mills were greatly influenced by the utilized raw materials and the applied paper chemical agents (flavor, coating materials and additives) in mills. (3) Gaseous pollution comparisons at common points. At the two common points in five mills, i.e. the wet end of paper machine and the wastewater treatment process, TVOC and HCHO, C x H y and H 2 S were the main gaseous pollutants, respectively. In addition, some feasible measures to realize a cleaner production in pulping and papermaking process were also put forward in the article. Highlights • We analyze the levels of 4 gaseous pollutants on 30 sites of 5 pulp & paper mills. • Gaseous pollution distinctions due to different production processes are studied. • Feasible measures to realize the cleaner production in the processes are suggested. • Gaseous pollution are greatly affected by raw materials and added paper chemicals. [ABSTRACT FROM AUTHOR]

In recent years, several studies have reported the recycling of by-products generated by the paper industry and their application to the construction industry. A majority of the existing studies used waste paper sludge ash, and considerable energy is consumed in such incineration processes. This may further contribute to air pollution. In this study, we used waste newspaper (WNP), which underwent a simple crushing process without a separate high-temperature treatment process, and we integrated it in cement mortar. We prepared mortars containing 0%, 0.2%, 0.4%, 0.6%, 0.8%, and 1.0% ground WNP as a cement substitute. Subsequently, the fluidity, compressive strength, tensile strength, carbonation depth, drying shrinkage, and microstructure of the mortars were compared and analyzed. The 28-day compressive strength of the mortar samples with WNP was approximately 3.2–16.1% higher than that of the control sample. The 28-day accelerated carbonation depth of the samples with WNP was approximately 1.03–1.61 mm. Furthermore, their carbonation resistance was approximately 5.2–39.4% higher than that of the control sample. Compressive strength, tensile strength, and carbonation resistance were improved by appropriately using ground WNP as a cement substitute in cement mortar. In this study, the appropriate amount of WNP according to the mechanical properties of cement mortar was found to be 0.4–0.8%, and considering the durability characteristics, the value 0.6 was the most ideal. [ABSTRACT FROM AUTHOR]

Accurate and quantitative profiling of air particulate matter (PM) compositions is essential for assessing local pollution information. The method combining mobile aerial sampling using unmanned aerial vehicles (UAVs) and prompt analysis excels in this regard as it allows spatiotemporal mapping of air pollution, especially in the vertical direction. However, applications of the method are still scarce as it is limited by a lack of sampling reliability due to insufficient aerial sampling time and a lack of accurate, portable quantification techniques. In this work, by integrating mobile aerial sampling with in-flight tethered charging and smartphone-based colorimetric analysis in a cost-effective paper microfluidic device, we present a method for quantitative, reliable profiling of spatiotemporal variation in air PM compositions. The method extends aerial sampling time to 12–15 flight hours per deployment, thereby significantly improving sampling reliability while maintaining the maneuverability of the UAVs. Also, smartphone-based colorimetric analysis combined with paper-based microfluidics enables portable, economically efficient analysis and is well-suited for using in low-resource settings. We demonstrated the utility of the method by carrying out a spatiotemporal variation study of air PM trace metal components (Fe, Ni, and Mn) at 4 geographical locations in Fuzhou, China, for a period of 21 days, and the results were in good agreement with results obtained from using a commercial instrument. Beside air PM composition study, this method is universally applicable and holds great potential to be extended to multipollutant analysis, such as prompt detection of airborne viruses, bacteria, and others. [ABSTRACT FROM AUTHOR]

Abstract On-site spatial variation study of airborne trace metals has been known to be the key to providing a comprehensive evaluation of air pollution information at any targeted location. However, the existing portable approaches either do not allow sample analysis in the longitudinal direction or is not yet practically applicable due to due to the lack of a portable detection method. In this paper, by integrating paper based colorimetric detection via cellphone and unmanned aerial vehicle (UAV) in-air sampling, we present an approach for on-site multiaxial quantification of airborne trace metals in an arrayed format. Using a self-built sampler mounting on a UAV, our approach enables automatic, multiaxial air PM sampling. In addition, by relying only on a cellphone and a custom-made field reaction kit, samples collected in-air can be readily processed, detected in an arrayed format and interpreted on-site within 30 min. Finally, an ultrafast batch-to-batch paper microfluidic chip fabrication protocol enables 48 chips to be fabricated under 30 s at a cost of 1.92 $, making the approach well-suited for disposable on-site use. Our system was first calibrated for 6 metals commonly found in airborne PM (i.e. Co, Cu, Fe, Mn, Cr and Ni), and the corresponding metals detection limits were found to be 8.16, 45.84, 1.86 × 102, 10.08, 1.52 × 102 and 80.40 ng. The validity of our approach was then demonstrated by characterizing 6 metals commonly found in air PM using a certified ash sample, and the experimentally determined metal weight percentage showed a good agreement with the manufacture certified value. Finally, the approach was used for on-site airborne trace metals spatial variation study at 4 difference locations in Fuzhou City (China), thus demonstrating the significance of our approach in supplementing air pollution information gathering and progressing rapid, on-site air toxicity assessment research. Graphical abstract Image 1 Highlights • Cellphone-based on-site quantification of airborne trace metals in an arrayed format. • High-throughput, automatic colorimetric images process using a self-developed app. • Automated multiaxial ambient pollutants sampling using a modified unmanned aerial vehicle. • Ultrafast batch-to-batch chip fabrication protocol to further reduce the cost per analysis. [ABSTRACT FROM AUTHOR]

The aim of the study was to evaluate the TAD of Akure, Ondo State, Nigeria. In this study, rainwater samples were collected monthly in a polyethylene container attached to a funnel for a period of twelve (12) months at 40 designated sites (residential, industrial, and traffic-related areas). The rainwater samples were filtered, the masses of TAD on the filter paper were determined gravimetrically, and atmospheric deposition rates were calculated. Meteorological data were measured at a monitoring site at the Department of Meteorology, Federal University of Technology, Akure, Ondo State, Nigeria. From the results obtained in this study, it was observed that deposition rated ranged between 5 and 427 μg/m². The average temperatures, wind speed, relative humidity, rainfall and wind direction for the periods were 25.00oC, 0.63 mph, 83.74%, 0.03mm and 117.43oC (2015) and 26.2 oC, 0.74mph, 81.89%, 0.92mm, 118.32o (2016). There were relationships between TAD and meteorological parameters. The results showed that TAD in many parts of the studied areas exceeded the World Health Organization guideline standards (350 μg/m²). [ABSTRACT FROM AUTHOR]

Simple Summary: Dairy farming is a significant source of pollutant gas emissions, contributing to climate change and air quality degradation. Understanding these emissions in milk production promotes productive efficiency and sustainable resource use. The aim of this paper is to provide a comprehensive analysis of ammonia and greenhouse gas emissions in dairy farming, utilizing bibliometric analysis methods. Articles featuring experimental data collection were selected, exclusively in English. The databases considered were Scopus and Web of Science. The analyses were conducted using Bibliometrix version 4.0.0 and VOSviewer version 1.6.20 tools to create knowledge maps visualizing information on research countries, institutions, author collaborations, and keyword networks. The search yielded 187 articles related to major pollutant gases such as methane, ammonia, carbon dioxide, nitrous oxide, and hydrogen sulfide. This study provided valuable insights into gas emission sources, air quality, environmental sustainability, and animal welfare, as well as identifying gaps and critical points in research on the topic. Ammonia and greenhouse gas emissions in dairy farming are crucial for climate change mitigation and sustainable agriculture. This research can contribute to academic interests while enhancing agricultural practices and informing environmental policies. The relevance of this research will persist with the growing demand for sustainable practices, as more researchers and organizations recognize the importance of gas emissions and mitigation research. A deeper understanding of gas emissions in milk production is crucial for promoting productive efficiency, sustainable resource use, and animal welfare. This paper aims to analyze ammonia and greenhouse gas emissions in dairy farming using bibliometric methods. A total of 187 English-language articles with experimental data from the Scopus and Web of Science databases (January 1987 to April 2024) were reviewed. Publications notably increased from 1997, with the highest number of papers published in 2022. Research mainly focuses on ammonia and methane emissions, including quantification, volatilization, and mitigation strategies. Other gases like carbon dioxide, nitrous oxide, and hydrogen sulfide were also studied. Key institutions include the University of California–Davis and Aarhus University. Bibliometric analysis revealed research evolution, identifying trends, gaps, and future research opportunities. This bibliometric analysis offers insights into emissions, air quality, sustainability, and animal welfare in dairy farming, highlighting areas for innovative mitigation strategies to enhance production sustainability. This research contributes to academia, enhancing agricultural practices, and informing environmental policies. It is possible to conclude that this research is a valuable tool for understanding the evolution of research on gas emissions in dairy cattle facilities, providing guidance for future studies and interventions to promote more sustainable production. [ABSTRACT FROM AUTHOR]

Various forms of pollution carry a substantial burden with respect to increasing the risk of causing and exacerbating noncommunicable diseases, especially cardiovascular disease. The first part of this 2-part series on pollution and cardiovascular disease provided an overview of the impact of global warming and air pollution. This second paper provides an overview of the impact of water, soil, noise, and light pollution on the cardiovascular system. This review discusses the biological mechanisms underlying these effects and potential environmental biometrics of exposure. What is clear from both these pollution papers is that significant efforts and redoubled urgency are needed to reduce the sources of pollution in our environment, to incorporate environmental risk factors into medical education, to provide resources for research, and, ultimately, to protect those who are particularly vulnerable and susceptible. [Display omitted] • Increasing evidence suggests that water, soil, noise, and light pollution increase cardiovascular morbidity and mortality. • The mechanisms linking these sources of pollution to cardiovascular disease are diverse, making mitigation efforts challenging, but evolving methods to track these sources of pollution may point to new strategies. • Collectively, these data underscore the urgent need to address pollution in all its forms at a global level. [ABSTRACT FROM AUTHOR]

This paper uses machine learning approaches to predict the association between traffic volume, air pollution, and meteorological conditions. A key focus is on the interaction between these factors. The paper does this using hourly traffic volume, N O x , P M 2.5 , and weather data for Oslo, Norway. I considered a total of six datasets of the 2019 whole-year data to verify the prediction accuracy of the models. I find that the autoregressive integrated moving average model with exogenous input variables, and the autoregressive moving average dynamic linear model outperform the machine learning models in predicting air pollution. At the same time, I also explored the effect of sampling weather subsets on prediction accuracy. Finally, my study makes optimal policy recommendations for reducing air pollution from traffic volume, after considering the interaction and lagged effects of meteorology, time variables, traffic, and air pollution. [ABSTRACT FROM AUTHOR]

Since 2013, Permitted Development Rights (PDR) in England have allowed commercial-to-residential conversions in locations once deemed suitable only for non-residential land-use. This deregulation of planning control has been justified as a way of encouraging more home-building in areas experiencing 'housing crisis', but its overall consequences remain unclear. This paper hence compiles quantitative evidence on a city-wide scale on the price, size, build and location of these conversions in London 2013–2021. It finds that homes produced through this route are generally smaller than the London average and are over-concentrated in neighbourhoods with fewer accessible green spaces and higher-than-average levels of air pollution. Here, larger conversion schemes (of more than 10 units) appear particularly problematic, potentially subjecting residents to forms of 'slow violence' that could have long-term consequences for their physical and mental health. The paper also finds that, on average, PDR conversions are marginally more affordable than other new developments in the capital, but are also more expensive per square metre, suggesting deregulation is allowing developers to 'extract' maximum value from these schemes rather than providing affordable homes per se. The implications of this are discussed in relation to the politics of housing in London and the wider forms of planning deregulation allowing developers to accrue increased profits from housing in an era of intense financialisation. [ABSTRACT FROM AUTHOR]

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 observed global climate change is an indisputable cause of the increased frequency of extreme weather events and related natural disasters. This phenomenon is observed all over the world including Poland. Moreover, Polish citizens as tourists are also exposed to climate phenomena that do not occur in our climate zone. Extreme weather events and related disasters can have a significant impact on people with allergic diseases, including asthma. These effects may be associated with the exposure to air pollution, allergens, and specific microclimate conditions. Under the auspices of the Polish Society of Allergology, experts in the field of environmental allergy prepared a statement on climate changes, natural disasters and allergy and asthma to reduce the risk of adverse health events provoked by climate and weather factors. The guidelines contain the description of the factors related to climate changes and natural disasters affecting the course of allergic diseases, the specific microclimate conditions and the recommendations of the Polish Society of Allergology for vulnerable population, patients suffering from asthma and allergy diseases, allergologists and authorities in the event of climate and weather hazards. [ABSTRACT FROM AUTHOR]

Rapid and selective sensing of sulfur dioxide (SO2) gas has attracted more and more attention because SO2 not only causes environmental pollution but also severely affects the health of human beings. Here we report an amino-functionalized luminescent metal-organic framework (MOF) material (i.e., MOF-5-NH2) and further investigate its sensing property for SO2 gas and its derivatives as a luminescent probe. The results indicate that the MOF-5-NH2 probe can selectively and sensitively sense SO2 derivatives (i.e., SO3 2-) in real time by a luminescence turn-on effect with a lower detection limit of 0.168 ppm and a response time of less than 15 s. Importantly, the luminescence turn-on phenomenon can be observed by the naked eye. We also assembled MOF-5-NH2 into a test paper to achieve the aim of portable detection, and the lower-limit concentration of the test paper for sensing SO2 in real time was found to be about 0.05 ppm. Moreover, MOF-5-NH2 also shows good anti-interference ability, strong luminescence stability, and reusability, which means that this material is an excellent sensing candidate. The amino functionalization may also provide a modification strategy to design luminescent sensors for other atmospheric pollutants. [ABSTRACT FROM AUTHOR]

Abstract: This paper tests whether adopting the international norm ISO 14001 significantly impacts environmental performance in Quebec''s pulp and paper industry. Using monthly data collected from 37 plants between 1997 and 2003, we show that: (i) ISO certification does not lead to a reduction in total suspended solid emissions or in quantity of rejected process water; (ii) discharge of biological oxygen demand decreases by about 9% following certification; (iii) contrary to the group of plants that did not adopt the ISO norm, the adopting plants did not experience a significant negative trend in emissions over our sample period. Moreover, our results show that the impact of ISO is very variable across adopting plants. If some plants considerably reduce emissions following certification, we find that most adopters either maintain or even increase emissions after being ISO accredited. [Copyright &y& Elsevier]

Deals with a study which investigated the uptake of air pollutants and their synergistic effects on paper. Chemical reactions involved in the adsorption of sulfur dioxide in paper; Experimental set up; Results; Discussion.

Due to concerns with air pollution and climate change, governments and transport operators around the world have engaged in transforming their fossil-fueled vehicles into electric vehicles (EVs). It is essential to build a model for the electrifying process to minimize the operation costs. This paper presents a systematic analytical approach for the electrification of a fire ambulance service station. This approach begins with the selection of suitable EVs to replace the current service vehicles. Subsequently, an in-depth analysis is conducted to determine the practical utilization of EVs at the station. The model proposes two charging strategies: immediate charging upon an EVs' return and smart charging. Based on the chosen EVs and charging strategies, a comprehensive assessment of the load profiles for the planned EV charging station is performed. In accordance with the load profiles, a mathematical model to minimize the infrastructure and operation costs of the charging station is proposed. Various pricing schemes are compared to identify the most efficient pricing scheme for the charging station, and economic analyses of the EVs and traditional ambulance vehicles are proposed in this paper. The test results indicate that the progressive pricing scheme is well suited for immediate charging strategies, whereas smart charging should opt for the time-of-use pricing scheme. Selecting the appropriate pricing scheme has the potential to significantly reduce electric energy costs. [ABSTRACT FROM AUTHOR]

Climatic and geographic factors characterizing local conditions, as well as the ecological state of the external environment, have a direct effect on human health, morbidity, and life expectancy. The paper considers the basic concepts of medical ecology, a pathogenetic role of environmental atmospheric pollution in the development of environmentally induced and environmentally dependent diseases associated with exposure to meteorological factors. In addition to the major hygienic risk factors affecting the public health (a level of air, water, and soil pollution), the levels of acoustic and electromagnetic background, the type of human nutrition, architectural and planning conditions of human life are of significant importance. Global climate warming causes numerous environmental changes, primarily an increase in surface air temperature, which in turn entails global changes in weather conditions that lead to various weather anomalies. Human health is directly dependent on environmental conditions and a degree of adaptation to them. The paper highlights the issues of diagnosing environmentally induced diseases and measures to counteract their spread. Based on the system diagnosis using physiological indicators of human health and the integration of the adaptation and nosological approaches, a hardware-software complex has been developed and introduced into medical practice. Corrective technologies of regenerative medicine that are used for ecologically dependent pathologies are described. Their application in the process of the complex sanatorium and resort treatment is most effective. [ABSTRACT FROM AUTHOR]

This study aimed to explore the published research on the relationship between climate change and skin cancer and the implications for prevention, management and further research. Scoping review. This scoping review following JBI methodology reviewed English articles identified in searches of MEDLINE, Embase, CINAHL, Web of Science and Scopus on 14 April 2023. The screening of articles was completed by two independent reviewers. Data were extracted by a single reviewer and checked by another. A causal pathway diagram was iteratively developed throughout the review and was used to categorise the findings. The search identified 1376 papers, of which 45 were included in the final review. Nine papers reported primary research, and 36 papers were reviews, perspectives, commentaries, editorials, or essays. The papers examined climate change influencing behaviours related to ultraviolet exposure (30 papers), ambient temperature (21 papers) and air pollution (five papers) as possible risk factors; occupational, rural, and contextual factors affecting skin cancer (11 papers); and prevention and access to health care in the context of climate change (seven papers). Most papers were published in journals in subject areas other than health. This review identified ultraviolet radiation, occupation, rising temperature, individual behaviour and air pollution as possible influences on skin cancer rates. Furthermore, it highlights the complexity and uncertainties in the relationship between climate change and skin cancer and the need for further research on this relationship, including primary epidemiological research and reviews that follow recognised review guidelines and include assessment of health services and social determinants in the causal pathways of this relationship. [ABSTRACT FROM AUTHOR]

Despite their key role in integrated waste management, direct (incineration) and indirect (gasification/pyrolysis) waste combustion processes are still opposed by some of the general public due to the past emission levels of air pollutants. In fact, although the release of air pollutants (especially dioxin) to the atmosphere from waste combustion processes has gradually decreased over the years, thanks to the introduction of stricter regulations and more advanced removal technologies, there is still an unsolved problem regarding the public acceptance of waste-to-energy facilities. The aim of this paper is to provide an overview of the state-of-the-art air pollution control (APC) technologies used in waste combustion facilities. Air pollution control technologies are designed to reduce or eliminate the emissions of harmful pollutants into the atmosphere. These technologies are important for safeguarding public health, protecting ecosystems, complying with regulations, and promoting a more sustainable and resilient future for both local and global communities. This paper will highlight the complexity behind emission control and the efforts made by this sector over the years. This paper will also propose suggested configurations based on the interactions/complementarity between different APC technologies and recent findings to improve their performance. [ABSTRACT FROM AUTHOR]

This paper investigates the influence of air pollution on irrational behaviors in stock trading through behavioral experiments in laboratory, simulating air pollution by burning straw and mosquito coils. The results of this study show that air pollution significantly improves disposition effect and repurchase effect in an asymmetric way, which are thought as irrational behaviors in stock investments, making subjects prefer selling winning stocks (part of disposition effect) and repurchasing stocks that have fallen in price since the sale (part of repurchase effect). Furthermore, regret, a negative emotion, is the psychological mechanism by which air pollution influences the irrational behaviors. [ABSTRACT FROM AUTHOR]

The concentration prediction of PM2.5 plays a vital role in controlling the air and improving the environment. This paper proposes a prediction model (namely EEMD-ALSTM) based on Ensemble Empirical Mode Decomposition (EEMD), Attention Mechanism and Long Short-Term Memory network (LSTM). Through the combination of decomposition and LSTM, attention mechanism is introduced to realize the prediction of PM2.5 concentration. The advantage of EEMD-ALSTM model is that it decomposes and combines the original data using the method of ensemble empirical mode decomposition, reduces the high nonlinearity of the original data, and Specially reintroduction the attention mechanism, which enhances the extraction and retention of data features by the model. Through experimental comparison, it was found that the EEMD-ALSTM model reduced its MAE and RMSE by about 15% while maintaining the same R2 correlation coefficient, and the stability of the model in the prediction process was also improved significantly. [ABSTRACT FROM AUTHOR]

Non-exhaust road transport emissions in cities contribute to poor air quality and have an impact on human health. This paper presents a new study of particles emitted by tyre wear in real driving conditions and gives their emission factors. The most frequently emitted particles were collected in urban, suburban and road areas. They were identified and analysed physically and chemically. Their level of toxicity is well known. An overall analysis of the measured pollutants was carried out to assess their emission factors in real driving situations. The highest emitting pollutants, considered separately, were found to have high emission factors. The values obtained exceed the Euro standard for vehicles but are below those of vehicles not equipped with particle filters. Significant test analysis confirmed that the inertia of chemical pollutants is homogeneous. Emission factors have also been provided for PM10 and PM2.5. These results should contribute to the emergence of future regulations of non-exhaust emissions and should help to analyse the exposure-impact relationship for particles from tyre wear. [ABSTRACT FROM AUTHOR]

Air pollution data provides important information on air quality, which can be used to assess the impact of atmospheric pollution on human health, the environment, and the economy, as well as to develop corresponding policies and measures to reduce pollutant emissions and improve air quality. In this paper, we propose a novel approach to improve the resolution of meteorological data via masked image modeling (PMIM) to generate high-resolution air pollution data. In order to apply the image masking modeling to process air pollution data, we convert the data format and use radial basis function visualization to generate smooth distribution maps of air pollution data. To generate high-resolution air pollution data, we design several different masking strategies and use the masked image modeling to simulate the reconstruction process from low-resolution grid data to high-resolution grid data, obtaining the reconstructed high-resolution grid images. Finally, we use the mapping relationship between the pixel colors of the reconstructed images and the air pollution data to generate high-resolution air pollution concentration data. In order to verify the effectiveness of the proposed method, we conduct comparative experiments using different masking strategies and test air pollution data of different resolutions. The results show that our method has good applicability and effectiveness in different situations. [ABSTRACT FROM AUTHOR]

• Quantifying the impact of peer pressure on environmental improvements among local governments in China. • Investigating cities ' reaction to declining air quality rankings through regression discontinuity design. • Demonstrating the efficacy of political incentives in combating pollution and the catalytic effect of rankings on policy action. • Assessing the benefits resulting from air pollution reductions using an exposure response function. This paper estimates the impact of peer governmental pressure on air quality using a regression discontinuity design inherent in China's air quality ranking system. Because air quality rankings are important for political evaluations, local officials who witnessed a decline in air quality ranking are motivated to enforce more stringent environmental standards compared to their counterparts with increased rankings. By exploiting this regulatory discontinuity with monthly air quality ranking data from 2012 to 2020 of 169 cities, we find that cities experiencing a lower air quality ranking in the current month compared to the previous month exhibit a subsequent improvement in air quality during the following month, as evidenced by decreased pollutant concentrations. Furthermore, our analysis reveals that in cities where pollutant rankings decline more sharply, officials are less likely to encounter fewer promotion opportunities. Importantly, we observe that the discontinuity in individual pollutant concentrations is not solely influenced by their respective rankings but is also impacted by the overall A ir Q uality I ndex (AQI) ranking. Linking the reduction in air pollutants concentration with the economic benefits, a back-of-the-envelope calculation indicates the decrease in premature deaths due to cardiovascular and respiratory diseases amounts to approximately 200 thousand, resulting in an associated economic saving of more than 600 billion Chinese yuan. [ABSTRACT FROM AUTHOR]

Variable selection involves selecting truly important predictors from p-dimensional multivariate functional predictors in functional predictive models. In this paper, a variable selection method is designed for scalar-on-function predictions entangled with nonlinear joint associations among scalar response and multiple functional predictors. First, a nonparametric functional nonlinear conditional correlation coefficient, namely, the FunNCC coefficient, is proposed to measure complex dependencies, including the nonmonotonic marginal dependence, along with the conditional associations of redundancy, complement, and interaction. Then, a model-free feature ordering and selection method is designed, where the FunNCC is utilized to rank relevance, enabling the selection of a subset of predictors with the strongest joint dependence. Since this method allows for quantitatively evaluating the contributions of predictors in explaining responses, it achieves moderate model interpretability. Finally, extensive simulation studies and two real-data cases involving air pollution regression and hand gesture recognition are conducted to evaluate the finite sample performance of the proposed method, and the results show that the proposed FunNCC and variable selection methods outperform state-of-the-art baselines. [ABSTRACT FROM AUTHOR]

In a global society that is increasingly interrelated and focused on mobility, carbon monoxide emissions derived from internal combustion vehicles remain the most important factor that must be addressed to improve environmental quality. Certainly, air pollution generated by internal combustion engines threatens human health and the well-being of the planet. In this regard, this paper aims to address the urgent need to understand and face the CO emissions produced by internal combustion vehicles; therefore, this work proposes a mathematical model based on Auto-Regressive Exogenous that predicts the CO percentages produced by an internal combustion engine during its start-up. The main goal is to establish a strategy for diagnosing excessive CO emissions caused by changes in the engine temperature. The proposed CO emissions modeling is evaluated under a real dataset obtained from experiments, and the obtained results make the proposed method suitable for being implemented as a novel diagnosis tool in automotive maintenance programs. [ABSTRACT FROM AUTHOR]

To explore the relationship between air pollution and total factor productivity and new pathways, This paper examines the impact of air pollution on total factor productivity of A-share listed companies in Shanghai and Shenzhen between 2015 and 2019. It investigates this relationship by considering two pathways: investor sentiment and government attention. The findings indicate that air pollution suppresses total factor productivity of firms. However, air pollution stimulates investor sentiment, which in turn increases R&D investment and total factor productivity, reducing to some extent the dampening effect of air pollution on total factor productivity. There exists a notable positive correlation between air quality and government attention, acting as a mediating variable. This implies that air pollution has the potential to capture the attention of governmental entities, leading to the implementation of appropriate measures aimed at managing and mitigating the occurrence of air pollution caused by industrial enterprises.And the relevant governments should formulate a series of policies to meet the different needs of different enterprises. These two approaches have varying impacts depending on the type of enterprises, thus governments should develop laws to cater to the various demands of different types of enterprises. [ABSTRACT FROM AUTHOR]

The Multi-Compartment Hg (mercury) Modeling and Analysis Project (MCHgMAP) is an international multi-model research initiative intended to simulate and analyze the geospatial distributions and temporal trends of environmental Hg to inform the effectiveness evaluations of two multilateral environmental agreements (MEAs): the Minamata Convention on Mercury (MC) and Convention on Long-Range Transboundary Air Pollution (LRTAP). This MCHgMAP overview paper presents its science objectives, background and rationale, experimental design (multi-model ensemble (MME) architecture, inputs and evaluation data, simulations and reporting framework), and methodologies for the evaluation and analysis of simulated environmental Hg levels. The primary goals of the project are to facilitate detection and attribution of recent (observed) and future (projected) spatial patterns and temporal trends of global environmental Hg levels, and identification of key knowledge gaps in Hg science and modeling to improve future effectiveness evaluation cycles of the MEAs. The current advances and challenges of Hg models, emission inventories, and observational data are examined, and an optimized multi-model experimental design is introduced for addressing the key policy questions of the MEAs. A common set of emissions, environmental conditions, and observation datasets are proposed (where possible) to enhance the MME comparability. A novel harmonized simulation approach between atmospheric, land, oceanic and multi-media models is developed to account for the short- and long-term changes in secondary Hg exchanges and to achieve mechanistic consistency of Hg levels across environmental matrices. A comprehensive set of model experiments is developed and prioritized to ensure a systematic analysis and participation of a variety of models from the scientific community. [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]

Bioaerosols are a subset of important airborne particulates that present a substantial human health hazard due to their allergenicity and infectivity. Chemical reactions in atmospheric processes can significantly influence the health hazard presented by bioaerosols; however, few studies have summarized such alterations to bioaerosols and the mechanisms involved. In this paper, we systematically review the chemical modifications of bioaerosols and the impact on their health effects, mainly focusing on the exacerbation of allergic diseases such as asthma, rhinitis, and bronchitis. Oxidation, nitration, and oligomerization induced by hydroxyl radicals, ozone, and nitrogen dioxide are the major chemical modifications affecting bioaerosols, all of which can aggravate allergenicity mainly through immunoglobulin E pathways. Such processes can even interact with climate change including the greenhouse effect, suggesting the importance of bioaerosols in the future implementation of carbon neutralization strategies. In summary, the chemical modification of bioaerosols and the subsequent impact on health hazards indicate that the combined management of both chemical and biological components is required to mitigate the health hazards of particulate air pollution. [ABSTRACT FROM AUTHOR]

Governments have implemented many regulations to solve traffic congestion and pollutant emissions. Traffic restriction (TR) policy is the most common and widely used traffic regulation. However, it is difficult to alleviate traffic pollution through TR policies. Only a few studies focus on TR policies in multiple cities. In this paper, we classify traffic restrictions by geographical factors and evaluate the impact of different policies based on PSM-DID first. Then, we classify the mixed restrictions and test their effects on air pollution. The results show that TR policy improves air quality regardless of the season. Moreover, the effect of TR policy is not affected by the superposition of the type of traffic restriction. For cities implementing the same TR policy, geographic factors can lead to different outcomes. This finding provides a reference for governments in reducing air pollution. • Traffic restrictions significantly affected air quality in different regions of China. • Cities implemented traffic restrictions have improved air quality in adjacent cities. • Effect of traffic restrictions does not depend on the number of mixed restrictions. [ABSTRACT FROM AUTHOR]

In this paper, the performance of a unidimensional continuous variable quantum key distribution protocol is analyzed using Gaussian modulated coherent state under fast fading channel. In the fast fading channel, both parties are connected in free space, resulting in a harsh propagation environment and pollution caused by atmospheric turbulence. This pollution makes it difficult for the communicators to determine the channel transmittance, which can only be estimated based on a probability distribution. To address this, only one modulator is used to code, which demonstrates performance equivalent to that of the symmetric modulated Gaussian coherent state protocol. The security of the protocol in the face of collective attacks is analyzed and it is proved that it can accept a certain amount of excessive channel noise while simplifying operations. Simultaneously, the impact of finite‐key length effects on the protocol is analyzed. It is also demonstrated that this protocol can reduce costs within an acceptable range of performance losses, making it more practical. [ABSTRACT FROM AUTHOR]

Recently, interest in wireless sensor networks (WSNs) and applications has grown significantly. The path loss caused by buildings and tall trees is a major obstacle in the distribution of sensor nodes. Because of absorption, dispersion, and attenuation by the structures or trees, a degradation occurs in the reliability of the communication link. In this paper, four path-loss models (PLMs) were developed for a LoRa (long-range) wireless sensor node mounted on the drone as a part of a WSN for monitoring air pollution over a distance of approximately 1,000 m utilising the received signal strength indicator (RSSI). Four novel PLMs were created using MATLAB's curve-fitting tools, employing polynomial (POLY), exponential (EXP), Gaussian, and power equations. To improve the accuracy of these equations, their coefficients were fine-tuned using the particle swarm optimisation (PSO) algorithm, resulting in the development of hybrid algorithms—EXP-PSO, POLY-PSO, Gaussian-PSO, and power-PSO. The results demonstrated that PSO-enhanced PLMs achieved an outstanding correlation coefficient (R2) value of 1, indicating their exceptional ability to represent PLMs accurately in the tested air population environment utilising WSNs. Notably, the POLY-PSO algorithm outperformed other algorithms, achieving the lowest root-mean-square error (RMSE) of 1.945 × 10−4 and sum of squares error (SSE) of 1.853 × 10−26. The PLMs based on hybridisation algorithms outperformed existing PLMs regarding the correlation coefficient. These findings hold significant implications for designing and optimising WSNs in air pollution applications, offering valuable insights into radio path-loss modelling in this area. [ABSTRACT FROM AUTHOR]

Comprehensive surveys conducted at 5-yr intervals were used to estimate sulfur dioxide (SO2) and nitrogen oxides (NOx) emissions from U.S. pulp and paper mills for 1980, 1985, 1990, 1995, 2000, and 2005. Over the 25-yr period, paper production increased by 50%, whereas total SO2 emissions declined by 60% to 340,000 short tons (t) and total NOx emissions decreased approximately 15% to 230,000 t. The downward emission trends resulted from a combination of factors, including reductions in oil and coal use, steadily declining fuel sulfur content, lower pulp and paper production in recent years, increased use of flue gas desulfurization systems on boilers, growing use of combustion modifications and add-on control systems to reduce boiler and gas turbine NOx emissions, and improvements in kraft recovery furnace operations. [ABSTRACT FROM AUTHOR]

Air pollution poses a grave threat to human health and everyday life. Accurate air-quality prediction plays a crucial role in effectively preventing and controlling air pollution. A multi-graph spatial-temporal attention network is proposed to predict the air quality in a given area by analyzing the interconnections between stations and the individual characteristics of each station. Firstly, this paper constructs multi-scale spatial-temporal graphs from spatial and temporal perspectives to effectively capture the interconnections between stations, thereby comprehensively understanding the spatial-temporal relationships among them. Secondly, incorporating the nonlinear temporal correlation of station data, this paper proposes a temporal multi-graph attention-fusion module to integrate information from both neighboring stations and the station itself. Finally, predictions are made using a spatial-temporal graph network. The experiments in this paper were based on air-quality data from Beijing and Tianjin, and the following experimental results were obtained. (1) The proposed model outperforms the baselines significantly in both single-step and multi-step prediction tasks. (2) The ablation study confirms that the graph constructed in this paper contributes to improving the performance of the model. (3) Comparing the performance of attention components, the proposed attention mechanism exhibits better performance than other attention mechanisms. [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]

Air pollution is worsening almost everywhere in the world. According to the Health Effects Institute (HEI), more than 95% of the world population breathe polluted air, toxic to their cardiovascular and respiratory health, which caused the death of 4.2 million people worldwide in 2016. As a result, the air pollution has become one of the leading causes of death worldwide. Therefore, an early cost-efficient warning system based on precise forecasting tools must be put in place to measure and avoid the harmful effects of exposure to the main air pollutants. Thus, it is essential to obtain reliable analytical information on air quality in a specific time and place. This paper focuses on monitoring air quality using a distributed intelligence which is a cost-efficient solution that enables a flexible prediction process distributed within a network of nodes and devices using a cross-platform solution. The suggested architecture enables collaborative learning along with collective knowledge graph building and knowledge sharing using the state of the art in Internet of Things, distributed machine learning, and ontologies. The proposed architecture suggests a flexible prediction system personalized for each node based on its need of information. Similar nodes get together for collective learning which allows for resource optimization, knowledge reusability, and device interoperability. The paper describes the modeling framework of distributed intelligence monitoring and analysis system designed for urban regions. [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]

1,3‐Butadiene is a carcinogenic and mutagenic air pollutant metabolized to butane epoxides, among which 1,2:3,4‐diepoxybutane (DEB) exhibits the highest genotoxicity. DEB is also formed by 1,3‐butadiene oxidation in the air, producing a direct environmental and occupational exposure. In this paper, we studied the kinetics of the nonenzymatic hydrolysis of DEB at a wide range of pH and temperature, including the catalytic effect of ionic species. The compound degradation involved a general and specific acid‐base catalysis of the epoxide ring hydrolysis. DEB had the greatest stability at pH 5–9, when the rates of acid‐catalyzed and base‐catalyzed hydrolysis are negligible and the neutral hydrolysis predominates. The capability of the buffer anions to accelerate the DEB decay increased in the order H2PO4− < HCO3− < CH3COO− < HPO42− < and CO32−. The Arrhenius equation well described the influence of temperature on the acid‐catalyzed, base‐catalyzed, and neutral hydrolysis rate constants. According to the obtained hydrolysis model coupled with the found thermodynamic parameters, the half‐life of DEB in natural fresh waters spans from 2 days at 30°C to 31 days at 0°C, but in the laboratory waste adjusted to pH 1or 13, the half‐life shortens to 2–3 h at 20°C. Therefore, the results of the paper help to assess the risk of exposure to the genotoxic action of DEB. [ABSTRACT FROM AUTHOR]

Background: Ambient air pollution can be harmful to the fetus even in countries with relatively low levels of pollution. Most of the established literature estimates the association between air pollution and health rather than causality. In this paper, I examine the causal effects of ambient air pollution on birth outcomes in Norway. Methods: With the large sample size and geographic division of sub-postal codes in Norway, I can control for a rich set of spatio-temporal fixed effects to overcome most of the endogeneity problems caused by the choice of residential area and date of delivery. After controlling for a rich set of spatio-temporal fixed effects, my paper uses the variance in ambient air pollutant concentrations over narrow time intervals and in a small geographic area of Norway to determine how prenatal air pollution exposure affects birth outcomes. My data contain extensive information about parents as well as meteorological conditions that can be used to control for potential confounding factors. Results: I find that prenatal exposure to ambient nitric oxide in the last trimester causes significant birth weight and birth length loss under the same sub-postcode fixed effects and calendar month fixed effects, whereas other ambient air pollutants such as nitrogen dioxide and sulfur dioxide appear to be at safe levels for the fetus in Norway. In addition, the marginal adverse effect of ambient nitric oxide is larger for newborns with disadvantaged parents. Both average concentrations of nitric oxide and occasional high concentration events can adversely affect birth outcomes. Conclusions: Prenatal exposure to NO pollution has an adverse effect on birth outcomes. This suggests that government and researchers should pay more attention to examining NO pollution and that health care providers need to advise pregnant women about the risks of air pollution during pregnancy. [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]

Air pollution is a critical problem in densely populated urban areas, with traffic significantly contributing. To mitigate the adverse effects of air pollution on public health and the environment, there is a growing need for the real-time monitoring and detection of pollution spikes in transportation. This paper presents a novel approach to using Internet of Things (IoT) edge networks for the real-time detection of air pollution peaks in transportation, specifically designed for innovative city applications. The proposed system uses IoT sensors in buses, cabs, and private cars. These sensors are equipped with air quality monitoring capabilities, including the measurement of pollutants such as particulate matter (PM2.5 and PM10), nitrogen dioxide (NO2), ozone (O3), sulfur dioxide (SO2), and carbon dioxide (CO2). The sensors continuously collect air quality data and transmit them to edge devices within the transportation infrastructure. The data collected by these sensors are analyzed, and alerts are generated when pollution levels exceed predefined thresholds. By deploying this system within IoT edge networks, transportation authorities can promptly respond to pollution spikes, improving air quality, public health, and environmental sustainability. This paper details the sensor technology, data analysis methods, and the practical implementation of this innovative system, shedding light on its potential for addressing the pressing issue of transportation-related pollution. The proposed IoT edge network for real-time air pollution spike detection in transportation offers significant advantages, including low-latency data processing, scalability, and cost-effectiveness. By leveraging the power of edge computing and IoT technologies, smart cities can proactively monitor and manage air pollution, leading to healthier and more sustainable urban environments. [ABSTRACT FROM AUTHOR]

Abstract: Burning joss paper, a common practice in temples in some Asian countries, can release toxic pollutants. This study investigated polychlorinated dibenzo-p-dioxin/dibenzofuran (PCDD/F) emissions and profiles from burning joss paper in a temple furnace connected to two wet scrubbers. The mean total PCDD/F content and corresponding toxic equivalent quantity (TEQ) in joss paper were 193 ng kg−1 and 0.645 ng I-TEQ kg−1, respectively, whereas those in bottom ash from burned joss paper were 18.5 ng kg−1 and 1.92 ng I-TEQ kg−1, respectively. The wet scrubbers decreased individual PCDD/F emissions by 26.7–71.0% and those of total PCDD/Fs and I-TEQ by 47.2% and 66.0%, respectively. The total PCDD/F TEQ emission factors before and after the wet scrubbers were 8.14 and 3.42 µg I-TEQ ton-feedstock−1, respectively. The estimated total PCDD/F and corresponding TEQ emissions were 5.29 g year−1 and 0.462 g I-TEQ year−1, respectively, in Taiwan. Burning joss paper in temple furnaces is a significant source of PCDD/F emissions. [Copyright &y& Elsevier]

This study introduces an applicable colorimetric sensor array for the detection of pesticides in the vapor phase. The array consisted of six metal nanoparticles spotted on the piece of filter paper. 3D-origami pattern was used for the fabrication of a paper-based sensor to decrease the effect of the nanoparticles leaching after exposure to analytes. Exposure to pesticide aerosols caused changes in the color of the array due to the aggregation of nanoparticles. These changes provided selective responses to thion pesticides such as malathion, parathion, chlorpyrifos, and diazinon. The sensing assay could also differentiate between aliphatic and aromatic thions and discriminate amine-containing compounds from the other studied analytes. These finding results are clearly confirmed by both visual detection and multivariate statistical methods. The proposed sensor was successfully developed for the quantitative measurement of pesticide aerosols at a very low concentration. The limit of detection of this method determined for malathion, parathion, chlorpyrifos and diazinon were 58.0, 103.0, 81.0 and 117.0, respectively. Moreover, the array could be employed to simultaneously analyze four studied pesticides. The statistcal results confirmed that the method has high performance for concurrent detection of thions as a major air pollutant without the interference of other species. [ABSTRACT FROM AUTHOR]

Abstract: Cooling tower emissions are harmful for several reasons such as air polluting, wetting, icing and solid particle deposition, but mainly due to human health hazards (i.e. Legionella). There are several methods for measuring drift drops. This paper is focussed on the sensitive paper technique, which is suitable in low drift scenarios and real conditions. The lack of an automatic classification method motivated the development of a digital image process algorithm for the Sensitive Paper method. This paper presents a detailed description of this method, in which, drop-like elements are identified by means of the Canny edge detector combined with some morphological operations. Afterwards, the application of a J48 decision tree is proposed as one of the most relevant contributions. This classification method allows us to discern between stains whose origin is a drop and stains whose origin is not a drop. The method is applied to a real case and results are presented in terms of drift and PM10 emissions. This involves the calculation of the main features of the droplet distribution at the cooling tower exit surface in terms of drop size distribution data, cumulative mass distribution curve and characteristic drop diameters. The Log-normal and the Rosin–Rammler distribution functions have been fitted to the experimental data collected in the tests and it can been concluded that the first one is the most suitable for experimental data among the functions tested (whereas the second one is less suitable). Realistic PM10 calculations include the measurement of drift emissions and Total Dissolved Solids as well as the size and number of drops. Results are compared to the method proposed by the U.S. Environmental Protection Agency assessing its overestimation. Drift emissions have found to be 0.0517% of the recirculating water, which is over the Spanish standards limit (0.05%). [Copyright &y& Elsevier]

This paper studies the effect of air pollution on voting outcomes. We use data from 60 federal and state elections in Germany from 2000 to 2018 and exploit plausibly exogenous fluctuations in ambient air pollution within counties across election dates. Higher air pollution on election day shifts votes away from incumbent parties and toward opposition parties. An increase in the concentration of particulate matter (PM10) by 10 g/m3--around two within-county SDs--reduces the vote share of incumbent parties by two percentage points, which is equivalent to 4% of the mean vote share. We generalize these findings by documenting similar effects with data from a weekly opinion poll and a large-scale panel survey. We provide further evidence that poor air quality leads to more negative emotions such as anger, worry, and unhappiness, which, in turn, may reduce the support for the political status quo. Overall, these results suggest that poor air quality affects decision-making in the population at large, including consequential political decisions. [ABSTRACT FROM AUTHOR]

Introduction: Curtis Bay (CB) is an environmental justice (EJ) community in South Baltimore. With a high concentration of industrial polluters and compounding non-chemical stressors, CB has experienced socioeconomic, quality of life, and health burdens for over 100 years. Today, these polluters include the open-air CSX Coal Terminal, waste-to-energy incinerators, and heavy diesel traffic through residential areas. The Community of Curtis Bay Association, Free Your Voice, and South Baltimore Community Land Trust are local organizations enacting a vision for equitable, healthy, and community-led development without industrial encroachment. In response to community-identified EJ concerns and an explosion at the CSX Coal Terminal, CB community groups partnered with academic researchers to develop a community-driven hyperlocal air monitoring and capacity building approach. This paper describes this approach to characterizing hyperlocal air quality in CB, building bridges between community residents and regulatory agencies, and nurturing a cohesive and effective community-academic partnership toward EJ. Methods: Using hyperlocal air monitoring, we are collecting real-time air pollution (particulate matter, black carbon, and ground-level gas species) and meteorological data from 15 low-cost sensors in residential and industrial areas of CB. We also use trail cameras to record activities at the CSX Coal Terminal. We merge air pollution and industrial activity data to evaluate the following: overall air quality in CB, multi-air pollutant profiles of elevated events, spatiotemporal changes in air quality in the community, patterns of industrial activity, and potential correlations between air quality and observed industrial activity. Members of our partnership also lead a high school course educating students about the history and ongoing efforts of the EJ movement in their community. Students in this course learn how to employ qualitative and quantitative data collection and analysis methods to bring scientific support to community EJ concerns. Results and Discussion: Our hyperlocal air monitoring network and community-academic partnership are continuing to evolve and have already demonstrated the ability to respond to community-identified EJ issues with real-time data while developing future EJ leaders. Our reflections can assist other community and academic groups in developing strong and fruitful partnerships to address similar EJ issues. [ABSTRACT FROM AUTHOR]