Integrating health on air quality assessment--review report on health risks of two major European outdoor air pollutants: PM and NO₂

Capturing Exposure Disparities with Chemical Transport Models: Evaluating the Suitability of Downscaling Using Land Use Regression

High resolution exposure surfaces are essential to capture disparities in exposure to traffic-related air pollution in urban areas. In this study, we develop an approach to downscale Chemical Transport Model (CTM) simulations to a hyperlocal level (∼100m) in the Greater Toronto Area (GTA) under three scenarios where emissions from cars, trucks and buses are zeroed out, thus capturing the burden of each transportation mode. This proposed approach statistically fuses CTMs with Land-Use Regression using machine learning techniques. With this proposed downscaling approach, changes in air pollutant concentrations under different scenarios are appropriately captured by downscaling factors that are trained to reflect the spatial distribution of emission reductions. Our validation analysis shows that high-resolution models resulted in better performance than coarse models when compared with observations at reference stations. We used this downscaling approach to assess disparities in exposure to nitrogen dioxide (NO2) for populations composed of renters, low-income households, recent immigrants, and visible minorities. Individuals in all four categories were disproportionately exposed to the burden of cars, trucks, and buses. We conducted this analysis at spatial resolutions of 12, 4, 1 km, and 100 m and observed that disparities were significantly underestimated when using coarse spatial resolutions. This reinforces the need for high-spatial resolution exposure surfaces for environmental justice analyses.

Fine particulate matter manipulates immune response to exacerbate microbial pathogenesis in the respiratory tract

Particulate matter with a diameter ≤2.5 μm (PM2.5) poses a substantial global challenge, with a growing recognition of pathogens contributing to diseases associated with exposure to PM2.5 Recent studies have focused on PM2.5, which impairs the immune cells in response to microbial infections and potentially contributes to the development of severe diseases in the respiratory tract. Accordingly, changes in the respiratory immune function and microecology mediated by PM2.5 are important factors that enhance the risk of microbial pathogenesis. These factors have garnered significant interest. In this review, we summarise recent studies on the potential mechanisms involved in PM2.5-mediated immune system disruption and exacerbation of microbial pathogenesis in the respiratory tract. We also discuss crucial areas for future research to address the gaps in our understanding and develop effective strategies to combat the adverse health effects of PM2.5.

The Impact of Air Pollution Controls on Health and Health Inequity Among Middle-Aged and Older Chinese: Evidence From Panel Data

Objectives

We evaluated the long-term effects of air pollution controls on health and health inequity among Chinese >45 years of age.

Methods

Data were derived from the China Health Aging and Retirement Longitudinal Survey and the China National Environmental Monitoring Centre. Decreases in PM2.5 and PM10 were scaled to measure air quality controls. We used a quasi-experimental design to estimate the impact of air quality controls on self-reported health and health inequity. Health disparities were estimated using the concentration index and the horizontal index.

Results

Air pollution controls significantly improved self-reported health by 20% (OR 1.20, 95% CI, 1.02-1.42). The poorest group had a 40% (OR 1.41, 95% CI, 0.96-2.08) higher probability of having excellent self-reported health after air pollution controls. A pro-rich health inequity was observed, and the horizontal index decreased after air pollution controls.

Conclusion

Air pollution controls have a long-term positive effect on health and health equity. The poorest population are the main beneficiaries of air pollution controls, which suggests policymakers should make efforts to reduce health inequity in air pollution controls.

Lag effect of ambient temperature on respiratory emergency department visits in Beijing: a time series and pooled analysis

BACKGROUND

Although the association between ambient temperature and mortality of respiratory diseases was numerously documented, the association between various ambient temperature levels and respiratory emergency department (ED) visits has not been well studied. A recent investigation of the association between respiratory ED visits and various levels of ambient temperature was conducted in Beijing, China.

METHODS

Daily meteorological data, air pollution data, and respiratory ED visits data from 2017 to 2018 were collected in Beijing. The relationship between ambient temperature and respiratory ED visits was explored using a distributed lagged nonlinear model (DLNM). Then we performed subgroup analysis based on age and gender. Finally, meta-analysis was utilized to aggregate the total influence of ambient temperature on respiratory ED visits across China.

RESULTS

The single-day lag risk for extreme cold peaked at a relative risk (RR) of 1.048 [95% confidence interval (CI): 1.009, 1.088] at a lag of 21 days, with a long lag effect. As for the single-day lag risk for extreme hot, a short lag effect was shown at a lag of 7 days with an RR of 1.076 (95% CI: 1.038, 1.114). The cumulative lagged effects of both hot and cold effects peaked at lag 0-21 days, with a cumulative risk of the onset of 3.690 (95% CI: 2.133, 6.382) and 1.641 (95% CI: 1.284, 2.098), respectively, with stronger impact on the hot. Additionally, the elderly were more sensitive to ambient temperature. The males were more susceptible to hot weather than the females. A longer cold temperature lag effect was found in females. Compared with the meta-analysis, a pooled effect of ambient temperature was consistent in general. In the subgroup analysis, a significant difference was found by gender.

CONCLUSIONS

Temperature level, age-specific, and gender-specific effects between ambient temperature and the number of ED visits provide information on early warning measures for the prevention and control of respiratory diseases.

Graphene-based chemiresistive gas sensors

Gas sensors allow the monitoring of the chemical environment of humans, which is often crucial for their wellbeing or even survival. Miniaturization, reversibility, and selectivity are some of the key challenges for serial use of chemical sensors. This tutorial review describes critical aspects when using nanomaterials as sensing substrates for the application in chemiresistive gas sensors. Graphene has been shown to be a promising candidate, as it allows gas sensors to be operated at room temperature, possibly saving large amounts of energy. In this review, an overview is given on the general mechanisms for gas-sensitive semiconducting materials and the implications of doping and functionalization on the sensing parameters of chemiresistive devices. It shows in detail how different challenges, like sensitivity, response time, reversibility and selectivity have been approached by material development and operation modes. In addition, perspectives from the area of data analysis and intelligent algorithms are presented, which can further enhance these sensors' usability in the field.

Long-term exposure to air pollution and mortality in Scotland: A register-based individual-level longitudinal study

BACKGROUND

Air pollution is associated with several adverse health outcomes. However, heterogeneity in the size of effect estimates between cohort studies for long-term exposures exist and pollutants like SO2 and mental/behavioural health outcomes are little studied. This study examines the association between long-term exposure to multiple ambient air pollutants and all-cause and cause-specific mortality from both physical and mental illnesses.

METHODS

We used individual-level administrative data from the Scottish-Longitudinal-Study (SLS) on 202,237 individuals aged 17 and older, followed between 2002 and 2017. The SLS dataset was linked to annual concentrations of NO2, SO2, and particulate-matter (PM10, PM2.5) pollution at 1 km2 spatial resolution using the individuals' residential postcode. We applied survival analysis to assess the association between air pollution and all-cause, cardiovascular, respiratory, cancer, mental/behavioural disorders/suicides, and other-causes mortality.

RESULTS

Higher all-cause mortality was associated with increasing concentrations of PM2.5, PM10, NO2, and SO2 pollutants. NO2, PM10, and PM2.5 were also associated with cardiovascular, respiratory, cancer and other-causes mortality. For example, the mortality hazard from respiratory diseases was 1.062 (95%CI = 1.028-1.096), 1.025 (95%CI = 1.005-1.045), and 1.013 (95%CI = 1.007-1.020) per 1 μg/m3 increase in PM2.5, PM10 and NO2 pollutants, respectively. In contrast, mortality from mental and behavioural disorders was associated with 1 μg/m3 higher exposure to SO2 pollutant (HR = 1.042; 95%CI = 1.015-1.069).

CONCLUSION

This study revealed an association between long-term (16-years) exposure to ambient air pollution and all-cause and cause-specific mortality. The results suggest that policies and interventions to enhance air quality would reduce the mortality hazard from cardio-respiratory, cancer, and mental/behavioural disorders in the long-term.

Tourism during health disasters: Exploring the role of health system quality, transport infrastructure, and environmental expenditures in the revival of the global tourism industry

Tourism is one of the most important promoters of sustainable development in many nations and regions around the globe. Tourism expansion has been a significant contributor to social and economic growth, particularly in developing economies. It is, however, vulnerable to all kinds of health crises and natural disasters, no matter how small they are. The primary purpose of this study is to acquire an empirical understanding of the effects of health crises and disasters on international tourism. The SYS-GMM was used to examine the impact of health calamities and crises, carbon footprints from transportation, and green finance on the tourism of 51 countries between 2007 and 2020. The results showed that health crises and natural disasters have a big effect on international tourism. Alternatively, the presence of eco-friendly and secure transportation at tourist destinations has a positive effect on the tourism industry. The results also showed that environmental expenditures have positive short- and long-term effects on international tourism. Furthermore, the sensitivity of travelers to health crises and natural disasters varies over the short and long term. The study also showed that compared to normal times, international tourism dropped by more than 67% during COVID-19. Consequently, this research assists us in comprehending, predicting, and preventing the potential adverse effects of COVID-19 and other similar economic, health disasters and crises that could occur in the future and harm the tourism industry.

Change-plane analysis for subgroup detection with a continuous treatment

Detecting and characterizing subgroups with differential effects of a binary treatment has been widely studied and led to improvements in patient outcomes and population risk management. Under the setting of a continuous treatment, however, such investigations remain scarce. We propose a semiparametric change-plane model and consequently a doubly robust test statistic for assessing the existence of two subgroups with differential treatment effects under a continuous treatment. The proposed testing procedure is valid when either the baseline function for the covariate effects or the generalized propensity score function for the continuous treatment is correctly specified. The asymptotic distributions of the test statistic under the null and local alternative hypotheses are established. When the null hypothesis of no subgroup is rejected, the change-plane parameters that define the subgroups can be estimated. This paper provides a unified framework of the change-plane method to handle various types of outcomes, including the exponential family of distributions and time-to-event outcomes. Additional extensions with nonparametric estimation approaches are also provided. We evaluate the performance of our proposed methods through extensive simulation studies under various scenarios. An application to the Health Effects of Arsenic Longitudinal Study with a continuous environmental exposure of arsenic is presented.

A Multi-Pollutant and Meteorological Analysis of Cardiorespiratory Mortality among the Elderly in São Paulo, Brazil-An Artificial Neural Networks Approach

Traditionally, studies that associate air pollution with health effects relate individual pollutants to outcomes such as mortality or hospital admissions. However, models capable of analyzing the effects resulting from the atmosphere mixture are demanded. In this study, multilayer perceptron neural networks were evaluated to associate PM₁₀, NO₂, and SO₂ concentrations, temperature, wind speed, and relative air humidity with cardiorespiratory mortality among the elderly in São Paulo, Brazil. Daily data from 2007 to 2019 were considered and different numbers of neurons on the hidden layer, algorithms, and a combination of activation functions were tested. The best-fitted artificial neural network (ANN) resulted in a MAPE equal to 13.46%. When individual season data were analyzed, the MAPE decreased to 11%. The most influential variables in cardiorespiratory mortality among the elderly were PM₁₀ and NO₂ concentrations. The relative humidity variable is more important during the dry season, and temperature is more important during the rainy season. The models were not subjected to the multicollinearity issue as with classical regression models. The use of ANNs to relate air quality to health outcomes is still very incipient, and this work highlights that it is a powerful tool that should be further explored.

A comprehensive overview of genotoxicity and mutagenicity associated with outdoor air pollution exposure in Brazil

This review examined the mutagenicity and genotoxicity associated with exposure to outdoor air pollutants in Brazil. A search was performed on the Web of Science database using a combination of keywords that resulted in 134 articles. After applying exclusion criteria, a total of 75 articles were obtained. The articles were classified into three categories: (1) studies with plants and animals, (2) in vitro studies, and (3) human biomonitoring. The investigations were conducted in 11 of 27 Brazilian states with the highest prevalence in the southeast and south regions. Only 5 investigations focused on the effects of burning biomass on the quality of outdoor air. Plants, especially Tradescantia pallida, were the main air pollution biomonitoring tool. When available, a significant association between levels of air pollutants and genetic damage was described. Among the in vitro studies, Salmonella/microsome is the most used test to evaluate mutagenesis of outdoor air in Brazil (n = 26). Human biomonitoring studies were the least frequent category (n = 18). Most of the investigations utilized micronucleus bioassay, in oral mucosa cells (n = 15) and lymphocytes (n = 5), and the comet assay (n = 6). The analysis in this study points to the existence of gaps in genotoxicity studies and our findings indicate that future studies need to address the variety of potential sources of pollution existing in Brazil. In addition to extent of the impacts, consideration should be given to the enormous Brazilian biodiversity, as well as the determination of the role of socioeconomic inequality of the population in the observed outcomes.

Evaluation of adaptive neuro-fuzzy inference system-genetic algorithm in the prediction and optimization of NOx emission in cement precalcining kiln

The increasing demand for cement due to urbanization growth in Africa countries may result in an upsurge of pollutants associated with its production. One major air pollutant in cement production is nitrogen oxides (NOx) and reported to cause serious damage to human health and the ecosystem. The operation of a cement rotary kiln NOx emission was studied with plant data using the ASPEN Plus software. It is essential to understand the effects of calciner temperature, tertiary air pressure, fuel gas, raw feed material, and fan damper on NOx emissions from a precalcining kiln. In addition, the performance capability of adaptive neuro-fuzzy inference systems and genetic algorithms (ANFIS-GA) to predict and optimize NOx emissions from a precalcining cement kiln is evaluated. The simulation results were in good agreement with the experimental results, with root mean square error of 2.05, variance account (VAF) of 96.0%, average absolute deviation (AAE) of 0.4097, and correlation coefficient of 0.963. Further, the optimal NOx emission was 273.0 mg/m³, with the parameters as determined by the algorithm were calciner temperature at 845 °C, tertiary air pressure - 4.50 mbar, fuel gas of 8550 m³/h, raw feed material 200 t/h, and damper opening of 60%. Consequently, it is recommended that ANFIS should be combined with GA for effective prediction, and optimization of NOx emission in cement plants.

Association of Combined Exposure to Ambient Air Pollutants, Genetic Risk, and Incident Rheumatoid Arthritis: A Prospective Cohort Study in the UK Biobank

BACKGROUND

Evidence for a potential link between air pollution and rheumatoid arthritis (RA) is inconsistent, and the modified effect of genetic susceptibility on the relationship between air pollution and RA has not been well studied.

OBJECTIVE

Using a general population cohort from the UK Biobank, this study aimed to investigate the associations between various air pollutants and the risk of incident RA and to further estimate the impact of combined exposure to ambient air pollutants on the risk of developing RA under the modification effect of genetic predisposition.

METHODS

A total of 342,973 participants with completed genotyping data and who were free of RA at baseline were included in the study. An air pollution score was constructed by summing the concentrations of each pollutant weighted by the regression coefficients with RA from single-pollutant models to assess the combined effect of air pollutants, including particulate matter (PM) with diameters ≤ 2.5 μ m (PM 2.5 ), between 2.5 and 10 μ m (PM 2.5 - 10 ), and ≤ 10 μ m (PM 10 ), as well as nitrogen dioxide (NO 2 ) and nitrogen oxides (NO x ). In addition, the polygenic risk score (PRS) of RA was calculated to characterize individual genetic risk. The Cox proportional hazard model was used to estimate hazard ratios (HRs) and 95% confidence intervals (95% CIs) of associations of single air pollutant, air pollution score, or PRS with incident RA.

RESULTS

During a median follow-up time of 8.1 y, 2,034 incident events of RA were recorded. The HRs (95% CIs) of incident RA per interquartile range increment in PM 2.5 , PM 2.5 - 10 , PM 10 , NO 2 , and NO x were 1.07 (1.01, 1.13), 1.00 (0.96, 1.04), 1.01 (0.96, 1.07), 1.03 (0.98, 1.09), and 1.07 (1.02, 1.12), respectively. We also found a positive exposure-response relationship between air pollution score and RA risk (p Trend = 0.000053 ). The HR (95% CI) of incident RA was 1.14 (1.00, 1.29) in the highest quartile group compared with the lowest quartile group of the air pollution score. Furthermore, the results of the combined effect of air pollution score and PRS on the RA risk showed that the risk of RA incidence in the highest genetic risk and air pollution score group was almost twice that of the lowest genetic risk and air pollution score group [incidence rate (IR) per 100,000 person-years: 98.46 vs. 51.19, and HR = 1.73 (95% CI: 1.39, 2.17) vs. 1 (reference)], although no statistically significant interaction between the air pollution and genetic risk for incident RA was found (p Interaction > 0.05 ).

DISCUSSION

The results revealed that long-term combined exposure to ambient air pollutants might increase the risk of RA, particularly in those with high genetic risk. https://doi.org/10.1289/EHP10710.

Nanoscale three-dimensional fabrication based on mechanically guided assembly

The growing demand for complex three-dimensional (3D) micro-/nanostructures has inspired the development of the corresponding manufacturing techniques. Among these techniques, 3D fabrication based on mechanically guided assembly offers the advantages of broad material compatibility, high designability, and structural reversibility under strain but is not applicable for nanoscale device printing because of the bottleneck at nanofabrication and design technique. Herein, a configuration-designable nanoscale 3D fabrication is suggested through a robust nanotransfer methodology and design of substrate's mechanical characteristics. Covalent bonding-based two-dimensional nanotransfer allowing for nanostructure printing on elastomer substrates is used to address fabrication problems, while the feasibility of configuration design through the modulation of substrate's mechanical characteristics is examined using analytical calculations and numerical simulations, allowing printing of various 3D nanostructures. The printed nanostructures exhibit strain-independent electrical properties and are therefore used to fabricate stretchable H₂ and NO₂ sensors with high performances stable under external strains of 30%.

A novel application of thermogravimetry-mass spectrometry for polystyrene quantification in the PM10 and PM2.5 fractions of airborne microplastics

Microplastics have appeared as emerging pollutants due to the diverse applications of plastics in today's world. Growing evidence points to the negative impacts that airborne microplastics have on human health, as they can enter the human body through respiration. Our aim was to quantify polystyrene airborne microplastics in smaller fractions, thoracic (PM₁₀) and alveolar (PM_2.5), as they have scarcely been studied. In this work, we proposed a methodology based on thermogravimetric analysis coupled with mass spectrometry that requires minimal sample preparation and does not limit particle size. We applied this methodology to quantify the airborne polystyrene in PM₁₀ and PM_2.5 fractions in mass units of microplastics per m³ of air in an urban and agricultural region during the summer of 2021. The mean concentrations of polystyrene found in the PM₁₀ and PM_2.5 fractions were 2.09 and 1.81 ng m^-3, respectively. Therefore, the majority of airborne polystyrene microplastics are found in the alveolar fraction which, is associated with severe cardiopulmonary and respiratory diseases. According to air mass backward trajectories, it was noted that the main sources of these emerging pollutants could be related to local agricultural practices.

Using low-cost sensors to assess real-time comfort and air quality patterns in indoor households

People spend most of their time in indoor environments without knowing about the air quality in these spaces. In this study, indoor low-cost sensors were used (for 5 months) to assess the comfort and air quality patterns in two indoor households. To strengthen the robustness of the considered approach and build confidence in the obtained comfort and indoor air quality (IAQ) levels, the sensor measurements were also compared against information from reference monitoring equipment; in which, high correlation coefficients were obtained (> 0.85) and also low errors (on average 22%). The IAQ results were strongly influenced by the residents' activity and behaviour, the outdoor weather conditions, and indoor/outdoor air pollution sources. Overall, the recommended values of temperature and relative humidity for the occupant's comfort in indoor environments were not fulfilled. The highest particulate matter (PM) levels were recorded at the weekend (on average +14% higher), while maximum CO₂ and CO levels were obtained on the weekdays (on average +9% higher). PM daily profiles followed the outdoor concentrations with the maximum levels at the end of the night and the lowest values in the early morning/mid-afternoon. The highest and lowest CO₂ concentrations were registered in the early morning (< 1536 ppm) and mid-afternoon (< 627 ppm), respectively, while the CO daily profiles showed a high impact of outdoor emissions, with the minimum concentrations up to 0.81 mg m^-3 (at 10 a.m. or 6 p.m.), and a maximum concentration of 1.87 mg m^-3 (at 10 p.m.). Real-time comfort conditions and IAQ levels are a powerful approach to providing fast decisions to minimise human exposure and prevent negative health impacts.

The impacts of reduction in ambient fine particulate (PM2.5) air pollution on life expectancy in Taiwan

Fine particulate matter, particles less than 2.5 um in diameter (PM_2.5), is an important environmental human health factor to consider. The long- and short-term influence of PM_2.5 on health has been extensively studied in relation to many health outcomes, although few investigations examined the consequences of chronic ambient PM_2.5 on life expectancy, which constitutes an important gauge of public human health status. Therefore, the aim of this study was to investigate the effects of reducing ambient PM_2.5 levels in Taiwan on life expectancy there from 2000 to 2020. Officially reported island-wide annually average concentrations of ambient PM_2.5, county-level life expectancies, and demographic and socioeconomic and proxy variable were collected for the prevalence of smoking from various national public agencies and organizations, since variables these might potentially confound life expectancy results. The relationship between changes in ambient PM_2.5 levels and life expectancy were determined using linear regression. Data demonstrated that counties with greater reductions in ambient PM_2.5 concentrations were associated with higher life expectancies. Adjusting for alterations in demographic and socioeconomic variables and proxy parameter, the prevalence of smoking data from a multiple regression model, it was found that a 0.3-year rise in life expectancy was noted for each 10 ug/m³ decrease in PM_2.5 in those counties. Our findings show that reducing ambient PM_2.5 levels play an important role for prolongation of life expectancy in Taiwan.

Synergistic or Antagonistic Health Effects of Long- and Short-Term Exposure to Ambient NO2 and PM2.5: A Review

Studies on adverse health effects associated with air pollution mostly focus on individual pollutants. However, the air is a complex medium, and thus epidemiological studies face many challenges and limitations in the multipollutant approach. NO2 and PM2.5 have been selected as both originating from combustion processes and are considered to be the main pollutants associated with traffic; moreover, both elicit oxidative stress responses. An answer to the question of whether synergistic or antagonistic health effects of combined pollutants are demonstrated by pollutants monitored in ambient air is not explicit. Among the analyzed studies, only a few revealed statistical significance. Exposure to a single pollutant (PM2.5 or NO2) was mostly associated with a small increase in non-accidental mortality (HR:1.01-1.03). PM2.5 increase of <10 µg/m3 adjusted for NO2 as well as NO2 adjusted for PM2.5 resulted in a slightly lower health risk than a single pollutant. In the case of cardiovascular heart disease, mortality evoked by exposure to PM2.5 or NO2 adjusted for NO2 and PM2.5, respectively, revealed an antagonistic effect on health risk compared to the single pollutant. Both short- and long-term exposure to PM2.5 or NO2 adjusted for NO2 and PM2.5, respectively, revealed a synergistic effect appearing as higher mortality from respiratory diseases.

Principles of risk decision-making

Risk management decisions in public health require consideration of a number of complex, often conflicting factors. The aim of this review was to propose a set of 10 fundamental principles to guide risk decision-making. Although each of these principles is sound in its own right, the guidance provided by different principles might lead the decision-maker in different directions. For example, where the precautionary principle advocates for preemptive risk management action under situations of scientific uncertainty and potentially catastrophic consequences, the principle of risk-based decision-making encourages decision-makers to focus on established and modifiable risks, where a return on the investment in risk management is all but guaranteed in the near term. To evaluate the applicability of the 10 principles in practice, one needs to consider 10 diverse risk issues of broad concern and explore which of these principles are most appropriate in different contexts. The 10 principles presented here afford substantive insight into the process of risk management decision-making, although decision-makers will ultimately need to exercise judgment in reaching appropriate risk decisions, accounting for all of the scientific and extra-scientific factors relevant to the risk decision at hand.

Assessment of the impact of sensor error on the representativeness of population exposure to urban air pollutants

For the monitoring of urban air pollution, smart sensors are often seen as a welcome addition to fixed-site monitoring (FSM) networks. Due to price and simple installation, increases in spatial representation are thought to be achieved by large numbers of these sensors, however, a number of sensor errors have been identified. Based on a high-resolution modelling system, up to 400 pseudo smart sensors were perturbated with the aim of simulating common sensor errors and added to the existing FSM network in Hong Kong, resulting in 1200 pseudo networks for PM_2.5 and 1040 pseudo networks for NO₂. For each pseudo network, population-weighted area representativeness (PWAR) was calculated based on similarity frequency. For PM_2.5, improvements (up to 16%) to the high baseline representativeness (PWAR = 0.74) were achievable only by the addition of high-quality sensors and favourable environmental conditions. The baseline FSM network represents NO₂ less well (PWAR = 0.52), as local emissions in the study domain resulted in high spatial pollution variation. Due to higher levels of pollution (population-weighted average 37.3 ppb) in comparison to sensor error ranges, smart sensors of a wider quality range were able to improve network representativeness (up to 42%). Marginal representativeness increases were found to exponentially decrease with existing sensor number. The quality and maintenance of added sensors had a stronger effect on overall network representativeness than the number of sensors added. Often, a small number of added sensors of a higher quality class led to larger improvements than hundreds of lower-class sensors. Whereas smart sensor performance and maintenance are important prerequisites particularly for developed cities where pollutant concentration is low and there is an existing FSM network, our study shows that for places with high pollutant variability and concentration such as encountered in some developing countries, smart sensors will provide benefits for understanding population exposure.

Analysis of the COVID-19 Lockdown’s Impact on Air Quality in the Larger Cities of Spain

During the period of the COVID-19 pandemic, the air quality reached the best levels to be recorded in large cities in Spain. To analyze and demonstrate this improvement in air quality levels, the evolution of the average nitrogen dioxide (NO2) levels in 78 Spanish cities with more than 50,000 inhabitants during the pre-COVID-19 years (2017–2019), the period of the COVID-19 lockdown, and the post-COVID-19 year (2021) was analyzed. The results show an improvement in the air quality in most of the cities analyzed for 2020 due to the COVID-19 restrictions. In addition, in 2021, without the COVID-19 restrictions, the air quality levels of the largest cities in Spain showed important improvements in terms of NO2 concentration compared to the levels in the pre-COVID-19 years (2017–2019). Nevertheless, in 2021, only 11 cities were below the average annual limit of 10 µg/m3 NO2 established by the World Health Organization (WHO). In addition, no cities with more than 500,000 inhabitants achieved NO2 levels below the WHO limit. Finally, a detailed monthly analysis indicated that the pre-COVID-19 levels were reached again during the last months of the monitored period.

Organic compound and particle emissions of additive manufacturing with photopolymer resins and chemical outgassing of manufactured resin products

Photopolymer resins are applied at an increasing rate in additive manufacturing (AM) industry as vat photopolymerization (VP) and material jetting (MJ) methods gain more popularity. The aim of this study was to measure volatile organic compound (VOC), carbonyl compound, ultrafine particle (UFP), and particulate matter (PM₁₀) air concentrations emitted in 3D printer operations. Individual chemicals were identified when multiple photopolymer resin feedstocks were used in various VP and MJ printers. The size distributions of UFPs, and indoor air parameters were also monitored. Finally, the VOC outgassing of the cured resin materials was determined over 84 days. The data demonstrated that 3D printer operators were exposed to low concentrations of airborne exposure agents as follows: average concentrations of VOCs were between 41 and 87 µg/m³, UFP number levels ranged between 0.19 and 3.62 × 10³ number/cm³; however, no impact was detected on air parameters or PM₁₀ concentrations. A majority of the UFPs existed in the 10-45 nm size range. The identified compounds included hazardous species included sensitizing acrylates and carcinogenic formaldehyde. The outgassed products included similar compounds that were encountered during the AM processes, and post-processing solvents. Products heated to 37°C emitted 1.4‒2.9-fold more VOCs than at room temperature. Total emissions were reduced by 84‒96% after 28 days roughly from 3000-14000 to 100-1000 µg/m²/hr. In conclusion, resin printer operators are exposed to low concentrations of hazardous emissions, which might result in adverse health outcomes during prolonged exposure. Manufactured resin products are suggested to be stored for 4 weeks after their production to reduce potential consumer VOC hazards.

An investigation on well-to-wheel emissions of passenger cars in Turkey

Passenger cars are responsible for a great amount of energy consumption and emissions in the world. Turkey is one of the world's twenty largest emission producers. The reason behind this study is to determine the most appropriate energy source for passenger cars particularly in Turkey in terms of main vehicle emissions. The results will be supportive for general inferences also. The impact of technological year, vehicle type, fuel type, fuel production, and electricity generation from different energy sources on well-to-wheel emissions for Turkey has been analyzed using the GREET software in this study. In the realization of emission analysis, transportation statistics of Turkey in the last 10 years have been evaluated. In addition, different scenarios have been presented for the years 2030 and 2050. It is found that average emissions emitted from passenger cars in Turkey decrease by year, and the use of LPG and CNG in plug-in hybrid cars generates lower emissions in future scenarios.

Prediction of highly vulnerable areas to COVID-19 outbreaks using spatial model: Case study of Cairo Governorate, Egypt

COVID-19 has affected over 170 countries around the world. Alarming rate has increased with the increase of infected cases and death rates. Whereas, the World Health Organization (WHO) had declared the COVID-19 virus as a pandemic on 11th March 2020. Preparations were made to face the spread of COVID-19, as predicting the most probable risk areas by using spatial models. Prediction spatial models of COVID-19 risk areas can help the governmental authorities to generate sustainable strategies and set up suitable protocols to control the pandemic. This research presents an attempt of a potential spatial prediction modeling of COVID-19 risk areas in Cairo governorate-Egypt. Four indicator models (demographic, residential, environmental and topographic) were developed using geomatics technology based on the guidelines of the UN-habitat sustainable development goals (SDGs) target (11 & 3). Five predicted scenarios were generated for the most pandemic probability areas by the integration of the four indicator models. The results showed that there are common areas in all scenarios for highly COVID-19 pandemic risk areas. These common risk areas were found in (El Marag, El Salam, Ain Shams, El Mataria, El Gammaleya, Manshiat Nasser, El Mosky, Bolak, Hadaak El Koba, and El Sharbeya) districts. The hotspots zones are characterized by overcrowding, high population density and economic activities, large family size, poor infrastructure service and low rate of education. Moreover, it was noticed that crowding points resulted in traffic density and air pollution, which may affect the pandemic spread. The accuracy assessment results displayed that, the environmental predicted scenario was more consistent with the official data of the Egyptian Ministry of Health and Population) MOHP), while the residential one was less convenient. The result of this study supports the health sector by predicting the hot spots areas. The present study is aimed to develop a proactive plan to confront the pandemic before spreading in the Cairo governorate-Egypt. Also, the proposed prediction model can be an effective aid for decision-makers across the world working on containment strategies to minimize the spread of Coronavirus.

Air pollution and trajectories of adolescent conduct problems: the roles of ethnicity and racism; evidence from the DASH longitudinal study

PURPOSE

No known UK empirical research has investigated prospective associations between ambient air pollutants and conduct problems in adolescence. Ethnic minority children are disproportionately exposed to structural factors that could moderate any observed relationships. This prospective study examined whether exposure to PM2.5 and NO2 concentrations is associated with conduct problems in adolescence, and whether racism or ethnicity moderate such associations.

METHODS

Longitudinal associations between annual mean estimated PM2.5 and NO2 concentrations at the residential address and trajectories of conduct problems, and the potential influence of racism and ethnicity were examined school-based sample of 4775 participants (2002-2003 to 2005-2006) in London, using growth curve models.

RESULTS

Overall, in the fully adjusted model, exposure to lower concentrations of PM2.5 and NO2 was associated with a decrease in conduct problems during adolescence, while exposure to higher concentrations was associated with a flattened trajectory of conduct symptoms. Racism amplified the effect of PM2.5 (β = 0.05 (95% CI 0.01 to 0.10, p < 0.01)) on adolescent trajectories of conduct problems over time. At higher concentrations of PM2.5, there was a divergence of trajectories of adolescent conduct problems between ethnic minority groups, with White British and Black Caribbean adolescents experiencing an increase in conduct problems over time.

CONCLUSION

These findings suggest that the intersections between air pollution, ethnicity, and racism are important influences on the development of conduct problems in adolescence.

Individual exposure to urban air pollution and its correlation with placental angiogenic markers in the first trimester of pregnancy, in São Paulo, Brazil

Pollution of the atmosphere is known that may lead to adverse obstetric outcomes, including fetal growth restriction, gestational hypertension, and preeclampsia. Such disorders are correlated with imbalances in angiogenic factors, which may also be involved in the pathological mechanism as the pollutants impact placental and maternal physiology. In the first trimester of gestation, this study assessed the outcomes of personal maternal short period exposure to air pollution on soluble fms-like tyrosine kinase 1 (sFlt1) and placental growth factor (PLGF) of pregnant women blood concentrations. This was a cross-sectional study, held in the city of São Paulo, Brazil, and conducted with low-risk pregnant women, who carried personal passive nitrogen dioxide (NO2) and ozone (O3) monitors for about a few days preceding the ultrasound evaluation, and on this day, the venous blood sample was collected to measure the angiogenic factors sFlt1 and PLGF and their ratio (sFlt1/PLGF) by enzyme-linked immunosorbent assay (ELISA). By means of multiple regression models, the effect of the studied pollutants on the log-transformed concentrations of the angiogenic factors was evaluated. One hundred thirty-one patients were included. The log of the sFlt1/PLGF ratio increased with rising NO2 levels (p = 0.021 and beta = 0.206), and the log of the PLGF concentration showed a negative correlation with NO2 (p = 0.008 and beta = - 0.234). NO2, an indicator of the levels of primary air pollutants, presented significant positive correlation with an increased sFlt1/PLGF ratio and diminished PLGF levels, which may reflect an antiangiogenic state generated by air pollution exposure.

The Influence of Air Pollutants and Meteorological Conditions on the Hospitalization for Respiratory Diseases in Shenzhen City, China

Air pollutants have significant direct and indirect adverse effects on public health. To explore the relationship between air pollutants and meteorological conditions on the hospitalization for respiratory diseases, we collected a whole year of daily major air pollutants’ concentrations from Shenzhen city in 2013, including Particulate Matter (PM₁₀, PM_2.5), Nitrogen dioxide (NO₂), Ozone (O₃), Sulphur dioxide (SO₂), and Carbon monoxide (CO). Meanwhile, we also gained meteorological data. This study collected 109,927 patients cases with diseases of the respiratory system from 98 hospitals. We investigated the influence of meteorological factors on air pollution by Spearman correlation analysis. Then, we tested the short-term correlation between significant air pollutants and respiratory diseases’ hospitalization by Distributed Lag Non-linear Model (DLNM). There was a significant negative correlation between the north wind and NO₂ and a significant negative correlation between the south wind and six pollutants. Except for CO, other air pollutants were significantly correlated with the number of hospitalized patients during the lag period. Most of the pollutants reached maximum Relative Risk (RR) with a lag of five days. When the time lag was five days, the annual average of PM₁₀, PM_2.5, SO₂, NO₂, and O₃ increased by 10%, and the risk of hospitalization for the respiratory system increased by 0.29%, 0.23%, 0.22%, 0.25%, and 0.22%, respectively. All the pollutants except CO impact the respiratory system’s hospitalization in a short period, and PM10 has the most significant impact. The results are helpful for pollution control from a public health perspective.

Emission Inventories and Particulate Matter Air Quality Modeling over the Pearl River Delta Region

The Pearl River Delta (PRD) region is located on the southeast coast of mainland China and it is an important economic hub. The high levels of particulate matter (PM) in the atmosphere, however, and poor visibility have become a complex environmental problem for the region. Air quality modeling systems are useful to understand the temporal and spatial distribution of air pollution, making use of atmospheric emission data as inputs. Over the years, several atmospheric emission inventories have been developed for the Asia region. The main purpose of this work is to evaluate the performance of the air quality modeling system for simulating PM concentrations over the PRD using three atmospheric emission inventories (i.e., EDGAR, REAS and MIX) during a winter and a summer period. In general, there is a tendency to underestimate PM levels, but results based on the EDGAR emission inventory show slightly better accuracy. However, improvements in the spatial and temporal disaggregation of emissions are still needed to properly represent PRD air quality. This study’s comparison of the three emission inventories’ data, as well as their PM simulating outcomes, generates recommendations for future improvements to atmospheric emission inventories and our understanding of air pollution problems in the PRD region.

Present cum future of SARS-CoV-2 virus and its associated control of virus-laden air pollutants leading to potential environmental threat - A global review

The world is presently infected by the biological fever of COVID-19 caused by SARS-CoV-2 virus. The present study is mainly related to the airborne transmission of novel coronavirus through airway. Similarly, our mother planet is suffering from drastic effects of air pollution. There are sufficient probabilities or evidences proven for contagious virus transmission through polluted airborne-pathway in formed aerosol molecules. The pathways and sources of spread are detailed along with the best possible green control technologies or ideas to hinder further transmission. The combined effects of such root causes and unwanted outcomes are similar in nature leading to acute cardiac arrest of our planet. To maintain environmental sustainability, the prior future of such emerging unknown biological hazardous air emissions is to be thoroughly researched. So it is high time to deal with the future of hazardous air pollution and work on its preventive measures. The lifetime of such an airborne virus continues for several hours, thus imposing severe threat even during post-lockdown phase. The world waits eagerly for the development of successful vaccination or medication but the possible outcome is quite uncertain in terms of equivalent economy distribution and biomedical availability. Thus, risk assessments are to be carried out even during the post-vaccination period with proper environmental surveillance and monitoring. The skilled techniques of disinfection, sanitization, and other viable wayouts are to be modified with time, place, and prevailing climatic conditions, handling the pandemic efficiently. A healthy atmosphere makes the earth a better place to dwell, ensuring its future lifecycle.

Identification of High Personal PM2.5 Exposure during Real Time Commuting in the Taipei Metropolitan Area

There has been an increase in the network of mass rapid transit (MRT) and the number of automobiles over the past decades in the Taipei metropolitan area, Taiwan. The effects of these changes on PM2.5 exposure for the residents using different modes of transportation are unclear. Volunteers measured PM2.5 concentrations while commuting in different modes of transportation using a portable PM2.5 detector. Exposure to PM2.5 (median (range)) was higher when walking along the streets (40 (10–275) µg/m3) compared to riding the buses (35 (13–65) µg/m3) and the cars (15 (8–80) µg/m3). PM2.5 concentrations were higher in underground MRT stations (80 (30–210) µg/m3) and inside MRT cars running in underground sections (80 (55–185) µg/m3) than those in elevated MRT stations (33 (15–35) µg/m3) and inside MRT cars running in elevated sections (28 (13–68) µg/m3) (p < 0.0001). Riding motorcycle also was associated with high PM2.5 exposure (75 (60–105 µg/m3), p < 0.0001 vs. walking). High PM2.5 concentrations were noted near the temples (588 ± 271 µg/m3) and in the underground food court of a night market (405 ± 238 µg/m3) where the eatery stalls stir-fried and grilled food (p < 0.0001 vs. walking). We conclude that residents in the Taipei metropolitan area may still be exposed to high PM2.5 during some forms of commuting, including riding underground MRT.

Long- and short-term time series forecasting of air quality by a multi-scale framework

Air quality forecasting for Hong Kong is a challenge. Even taking the advantages of auto-regressive integrated moving average and some state-of-the-art numerical models, a recently-developed hybrid method for one-day (two- and three-day) ahead forecasting performs similarly to (slightly better than) a simple persistence forecasting. Long-term forecasting also remains an important issue, especially for policy decision for better control of air pollution and for evaluation of the long-term impacts on public health. Given the well-recognized negative effects of PM_2.5, NO₂ and O₃ on public health, we study their time series under the multi-scale framework with empirical mode decomposition and nonstationary oscillation resampling to explore the possibility of long-term forecasting and to improve short-term forecasts in Hong Kong. Applied to a dataset from January 2016 to December 2018, the long-term forecasting (with lead time about 100 days) of the multi-scale framework has the root-mean-square error (RMSE) comparable with that of the short-term (with lead time of one or two days) forecasting by the persistence method, while its improvement for short-term forecasting (with lead time of one, two or three days) is quite substantial over the persistence forecasting, with RMSEs reduced by respectively 44%-47%, 30%-45%, and 40%-60% for PM_2.5, NO₂, and O₃. Compared to the hybrid method, it turns out that, for short-term forecasting for the same data, the multi-scale framework can reduce RMSE by about 25% (respectively 30%) for PM_2.5 (respectively NO₂ and O₃). In addition, we find no significant difference in the forecasting performance of the multi-scale framework among different types of stations. The multi-scale framework is feasible for time series forecasting and applicable to other pollutants in other cities.

Seasonal Variations of Fine Particulate Matter and Mortality Rate in Seoul, Korea with a Focus on the Short-Term Impact of Meteorological Extremes on Human Health

Rapid industrialization of Korea’s economy has brought with it environmental pollution that threatens human health. Among various other pollutants, ambient fine particulate matter known to endanger human health often exceeds air quality standards in Seoul, South Korea’s capital. The goal of this research is to find the impact of meteorological extremes and particle levels on human health. The analysis was conducted using hourly air pollutant concentrations, meteorological variables, and the daily mortality from cerebrovascular disease. Results show that the effect of fine particulate matter on mortality from cerebrovascular disease was more noticeable during meteorological extremes. The linkage between extreme weather conditions and mortality was more apparent in winter than in summer. Comprehensive studies of various causes of diseases should be continued to more accurately analyze the effects of fine particulate matter on human health and meteorological extremes, and to further minimize the public health impact of air pollution and meteorological conditions.

Fine Particulate Matter (PM2.5) and Chronic Kidney Disease

The impact of ambient particulate matter (PM) on public health has become a great global concern, which is especially prominent in developing countries. For health purposes, PM is typically defined by size, with the smaller particles having more health impacts. Particles with a diameter <2.5 μm are called PM_2.5. Initial research studies have focused on the impact of PM_2.5 on respiratory and cardiovascular diseases; nevertheless, an increasing number of data suggested that PM_2.5 may affect every organ system in the human body, and the kidney is of no exception. The kidney is vulnerable to particulate matter because most environmental toxins are concentrated by the kidney during filtration. According to the high morbidity and mortality related to chronic kidney disease, it is necessary to determine the effect of PM_2.5 on kidney disease and its mechanism that needs to be identified. To understand the current status of PM_2.5 in the atmosphere and their potential harmful kidney effects in different regions of the world this review article was prepared based on peer-reviewed scientific papers, scientific reports, and database from government organizations published after the year 1998. In this review, we focus on the worldwide epidemiological evidence linking PM_2.5 with chronic kidney disease and the effect of PM_2.5 on the chronic kidney disease (CKD) progression. At the same time, we also discuss the possible mechanisms of PM_2.5 exposure leading to kidney damage, in order to emphasize the contribution of PM_2.5 to kidney damage. A global database on PM_2.5 and kidney disease should be developed to provide new ideas for the prevention and treatment of kidney disease.

Changes in outdoor air pollution due to COVID-19 lockdowns differ by pollutant: evidence from Scotland

Objectives

To examine the impact of COVID-19 lockdown restrictions in March/April 2020 on concentrations of nitrogen dioxide (NO2) and ambient fine particulate matter (PM2.5) air pollution measured at roadside monitors across Scotland by comparing data with previous years.

Methods

Publicly available data of PM2.5 concentrations from reference monitoring systems at sites across Scotland were extracted for the 31-day period immediately following the imposition of lockdown rules on 23 March 2020. Similar data for 2017, 2018 and 2019 were gathered for comparison. Mean period values were calculated from the hourly data and logged values compared using pairwise t-tests. Weather effects were corrected using meteorological normalisation.

Results

NO2 concentrations were significantly lower in the 2020 lockdown period than in the previous 3 years (p<0.001). Mean outdoor PM2.5 concentrations in 2020 were much lower than during the same period in 2019 (p<0.001). However, despite UK motor vehicle journeys reducing by 65%, concentrations in 2020 were within 1 µg/m3 of those measured in 2017 (p=0.66) and 2018 (p<0.001), suggesting that traffic-related emissions may not explain variability of PM2.5 in outdoor air in Scotland.

Conclusions

The impact of reductions in motor vehicle journeys during COVID-19 lockdown restrictions may not have reduced ambient PM2.5 concentrations in some countries. There is also a need for work to better understand how movement restrictions may have impacted personal exposure to air pollutants generated within indoor environments.

Modelling air quality levels of regulated metals: limitations and challenges

Toxic metals as arsenic (As), cadmium (Cd), nickel (Ni), and lead (Pb) exist in the atmosphere as particulate matter components. Their concentration levels in the European Union (EU) are regulated by European legislation, which sets target and limit values as annual means, and by the World Health Organization (WHO) that defines guidelines and reference values for those metal elements. Modelling tools are recommended to support air quality assessment regarding the toxic metals; however, few studies have been performed and those assessments rely on discrete measurements or field campaigns. This study aims to evaluate the capability of air quality modelling tools to verify the legislation compliance concerning the atmospheric levels of toxic elements and to identify the main challenges and limitations of using a modelling assessment approach for regulatory purposes, as a complement to monitoring. The CAMx air quality model was adapted and applied over Porto and Lisbon urban regions in Portugal at 5 × 5-km2 and 1 × 1-km2 horizontal resolution for the year 2015, and the results were analysed and compared with the few measurements available in three locations. The comparison between modelled and measured data revealed an overestimation of the model, although annual averages are much lower than the regulated standards. The comparison of the 5-km and 1-km resolutions' results indicates that a higher resolution does not necessarily imply a better performance, pointing out uncertainties in emissions and the need to better describe the magnitude and spatial allocation of toxic metal emissions. This work highlighted that an increase of the spatial and temporal coverage of monitoring sites would allow to improve the model design, contribute to a better knowledge on toxic metals atmospheric emission sources and to increase the capacity of models to simulate atmospheric particulate species of health concern.

Willingness to Pay for Urban Heat Island Mitigation: A Case Study of Singapore

In many countries, urban heat island (UHI) effects come along with urbanization in metropolitan areas. They have relevant adverse effects on the health and wellbeing of citizens. Singapore is strongly affected by UHI. In this study, we assess Singaporeans’ willingness to pay (WTP) for UHI mitigation by implementing a contingent valuation analysis. Specifically, we employ a double-bounded dichotomous survey design on a representative sample of 1822 online respondents. We find that Singaporeans are willing to sacrifice on average 0.43% of their annual income to mitigate UHI. The total WTP for mitigation strategies among Singapore citizens and permanent residents is estimated at SGD$783.08 million per year, the equivalent of USD$563.80 per year. Our findings suggest that there is a positive and significant relationship between the size of UHI effects and the citizens’ WTP. People living in the region with the highest intensity of UHI are willing to pay 3.09 times more than those living in the region with the lowest UHI intensity. Furthermore, demographic and socio-economic characteristics are significant determinants of Singaporeans’ WTP. The WTP increases with income and education but decreases with age. Students, men, and people with children are willing to pay more. Additional analyses show that the level of UHI awareness, positive attitudes towards UHI mitigation strategies as well as preferences for outdoor activities are positively correlated with the WTP. Our findings suggest that citizens are aware of the impacts of UHI and support UHI mitigation measures to be financed by their taxes. Policy interventions to promote UHI-related education and disseminating UHI-related information might increase the support of UHI mitigation policies.

Inhibitory effect of particulate matter on toll-like receptor 9 stimulated dendritic cells by downregulating mitogen-activated protein kinase and NF-κB pathway

Ambient particulate matter (PM) is associated with adverse health consequences. However, the influence of PM on the innate immune system is poorly understood. The aim of the present study was to examine the effect of diesel particulate matter 2.5 μm (PM_2.5, SRM1650b) on dendritic cells. PM_2.5 significantly reduced cytokine levels of interleukin (IL)-12 p40, IL-6 and TNF-α levels in CpG-DNA (TLR9 ligand)-stimulated dendritic cells. To determine the mechanisms underlying this observed inhibition induced by PM_2.5, western blot analysis was conducted. PM_2.5 was found to downregulate ERK1/2, JNK1/2, p38 MAPKs, and NF-κB pathways. PM_2.5 exposure decreased TLR9-dependent NF-κB and activator protein (AP-1) reporter luciferase activities. Our findings demonstrate that PM_2.5 reduced the production of cytokines which may be associated with inhibition of MAPK and NF-κB signaling pathway. Further, data suggest the immunosuppressive effect of PM_2.5 on the innate immune cells may lead to serious damage to the host immune system.

Relationship of chronic kidney disease with major air pollutants - A systematic review and meta-analysis of observational studies

BACKGROUND

Articles concerning the correlation of the risk of chronic kidney disease (CKD) with air contaminant exposure present inconsistent findings and the magnitude of the link is still unclear. Therefore, we planned to systematically and quantitatively investigate the overall strength of proofs in this field.

METHODS

Relevant articles on Cochrane, EMBASE, Medline, Web of Science, and CINHAL were searched as per relevant strategies. Only observational studies that disclosed the link of CKD risk with major air pollutants were enrolled, including PM10 and PM2.5, which were particulate matter less than 10 um and less than 2.5 um in erodynamic diameter respectively. Pooled relative risk (RR) and 95 % confidence interval (CI) were determined using random--effects models, regardless of the heterogeneity quantified by I² statistic.

RESULTS

Finally, 7 studies involving 5,812,381 participants were included. The incidence of CKD was increased by long-term exposure to PM10 (including solely estimated exposure to PM10 from studies using PM2.5) (RR 1.08, 95 %CI 1.04-1.11) with considerable heterogeneity (I² = 79 %), and the risk of CKD was raised by 8% when the long-time exposure to PM10 increased by 10 ug/m³. The pooled RR (95 %CI) with a 10 μg/m³ increase in PM2.5 for risk of CKD was 1.09 (1.03-1.17). Stratified analysis also verified the general negative effects.

CONCLUSIONS

Chronic subjection to major air contaminants (PM10 and PM2.5) is more likely to cause CKD. Thus, developing global approaches of air pollution elimination to prevent CKD is urgent.

Air-Pollution Control in an Emergent Market: Does It Work? Evidence from Romania

Economic development in a national and international context must be based on a sustainability strategy established on the systemic interaction between the economic, sociocultural, and ecological environments. Today, the world is confronted by many challenges related to climate change and natural-resource flows, including waste streams resulting from economic activity. The need for national and European environmental standards and the work of an environment monitoring authority to reduce air pollution are highlighted by economic and industrial activities. Thus, our research focused on determining if emissions of sulfur dioxide (SO₂), nitrogen (NO₂), and particulate matter 10 (PM₁₀) are influenced by planned and unplanned inspections made by competent authorities from Romania. We built a regression model that estimates the influence of economic measures imposed by the authorities on reducing industrial air pollution. Preliminary results showed that the number of inspections negatively influences air pollution, indicating that national and local authorities in Romania are striving to maintain air quality and are conducting more inspections when air pollution is high.

A Functional Data Analysis Approach for the Detection of Air Pollution Episodes and Outliers: A Case Study in Dublin, Ireland

Ground level concentrations of nitrogen oxide (NOx) can act as an indicator of air quality in the urban environment. In cities with relatively good air quality, and where NOx concentrations rarely exceed legal limits, adverse health effects on the population may still occur. Therefore, detecting small deviations in air quality and deriving methods of controlling air pollution are challenging. This study presents different data analytical methods which can be used to monitor and effectively evaluate policies or measures to reduce nitrogen oxide (NOx) emissions through the detection of pollution episodes and the removal of outliers. This method helps to identify the sources of pollution more effectively, and enhances the value of monitoring data and exceedances of limit values. It will detect outliers, changes and trend deviations in NO2 concentrations at ground level, and consists of four main steps: classical statistical description techniques, statistical process control techniques, functional analysis and a functional control process. To demonstrate the effectiveness of the outlier detection methodology proposed, it was applied to a complete one-year NO2 dataset for a sub-urban site in Dublin, Ireland in 2013. The findings demonstrate how the functional data approach improves the classical techniques for detecting outliers, and in addition, how this new methodology can facilitate a more thorough approach to defining effect air pollution control measures.

Integrating road traffic externalities through a sustainability indicator

Road traffic poses negative externalities on society and represents a key challenge in sustainable transportation. However, the existing literature about the assessment of traffic externalities drawn on a common measure is scarce. This paper develops a sustainability indicator that integrates traffic-related externalities as means of traffic congestion, noise, greenhouse gases (GHG) and nitrogen oxides emissions, health impacts and road crash related costs, and adjusted to local contexts of vulnerability. Traffic, road crashes, acoustic and vehicle dynamic data were collected from one real-world intercity corridor pair comprising three alternative routes. The site-specific operations were characterized using a modeling platform of traffic, emissions, noise and air quality. A specific methodology is applied for each road traffic externality and translated in a single factor - external cost. The results indicated that road crashes presented the largest share in the partly rural/urban route while GHG emissions had the highest contribution in external costs for the highway routes. Also, the distribution of external cost component varied according to the type of road, mostly due to different levels of exposed inhabitants. This paper offers a line of research that produced a method for decision-makers with a reliable and flexible cost analysis aimed at reducing the negative impacts of road traffic. It also encourages the design of eco-traffic management policies considering the perspective of drivers, commuters and population.

Cardio-respiratory health effects of exposure to traffic-related air pollutants while exercising outdoors: A systematic review

Despite physical exercise provides numerous health benefits, outdoor exercisers are frequently exposed to traffic-related air pollutants (TRAP) known to be associated with respiratory and cardiovascular diseases. The aim of this systematic review was to investigate the effects of TRAP exposure, specifically particulate matter and nitrogen dioxide (NO₂), during outdoor exercise on cardio-respiratory health effects. Systematic database searches of PubMed, Web of Science, Scopus and Medline were performed by two researchers to identify peer-reviewed studies from 2000 to 2018. Combinations of keywords related to cardio-respiratory health effects, physical exercise and ambient air pollution were used. Thirteen studies were included, originating predominantly from European countries but also the American. They suggested that exercising in an environment with high TRAP exposure increases markers of respiratory and systemic inflammation, as well as, impairs the vascular function and increases artery pressure, when compared with an environment with low-TRAP exposure. In addition, the smaller particles appear to have the most severe health consequences compared with the larger coarse particles and NO₂. This study also provides evidence that specific groups of the population have enhanced susceptibility to adverse effects from particulate matter exposure while exercising. There is a need for more studies focused on the relationship between air pollution, physical exercise and health, as large societal benefits can be obtained from healthy environments that can promote outdoor physical exercise.

Monthly-Term Associations Between Air Pollutants and Respiratory Morbidity in South Brazil 2013-2016: A Multi-City, Time-Series Analysis

Most air pollution research conducted in Brazil has focused on assessing the daily-term effects of pollutants, but little is known about the health effects of air pollutants at an intermediate time term. The objective of this study was to determine the monthly-term association between air pollution and respiratory morbidity in five cities in South Brazil. An ecological time-series study was performed using the municipality as the unit of observation in five cities in South Brazil (Gravataí, Triunfo, Esteio, Canoas, and Charqueadas) between 2013 and 2016. Data for hospital admissions was obtained from the records of the Hospital Information Service. Air pollution data, including PM₁₀, SO₂, CO, NO₂, and O₃ (µg/m³) were obtained from the environmental government agency in Rio Grande do Sul State. Panel multivariable Poisson regression models were adjusted for monthly counts of respiratory hospitalizations. An increase of 10 μg/m³ in the monthly average concentration of PM₁₀ was associated with an increase of respiratory hospitalizations in all age groups, with the maximum effect on the population aged between 16 and 59 years (IRR: Incidence rate ratio 2.04 (95% CI: Confidence interval = 1.97–2.12)). For NO₂ and SO₂, stronger intermediate-term effects were found in children aged between 6 and 15 years, while for O₃ higher effects were found in children under 1 year. This is the first multi-city study conducted in South Brazil to account for intermediate-term effects of air pollutants on respiratory health.

Relationship between Air Pollution and Regional Longevity in Guangxi, China

Air pollution has become a global environmental challenge and poses major threats to human health, particularly for the aging population. However, few studies have investigated the effects of air pollutants on human longevity, especially based on the total regional quantities and sources. Based on investigation of the spatiotemporal variations of three air pollutants (PM₁₀, SO₂, and NOx) and three longevity indicators (centenarian ratio, centenarity index, and aging tendency), this study aims to identify the relationship between air pollution and regional longevity in Guangxi Province. Air pollutant and population data from 109 counties and areas of Guangxi were collected from environmental research reports and statistical yearbooks. Cluster and outlier analysis was used to detect the regions with high and low clusters of the longevity indicators and air pollutants. Geographically weighted regression analyses were performed to determine the relationship between longevity and air pollutants. A negative relationship between the air pollutants PM₁₀, SO₂, and NOx on the aged population was observed. From a provincial level, industrial sources from the urban areas of cities located in the central province, including Liuzhou, Nanning, Laibing, Guigang and Yulin, were important contributors to the air pollutants PM₁₀, SO₂, and NOx, and thus could contribute to negative impacts on regional longevity. The key findings from this study will provide a case for management of air pollutants based on public health policies in China as well as other developing communities.

Relationship between fine particulate air pollution exposure and human adult life expectancy in Taiwan

Among the air pollutants, particulate matter with an aerodynamic diameter less than 2.5 um (PM_2.5) is of particular interest to environmental medicine as epidemiologic studies consistently reported that long-term exposure to PM_2.5 is associated with increased risk of premature death in adults. Life expectancy is a well-documented and important measure of overall public health policy. However, few investigators examined the relationship between PM_2.5 levels and adult life expectancy. In this Taiwan-wide study, county-level annual mean PM_2.5 concentrations data were collected concomitantly with potential confounding variables including demographic and socioeconomic status, as well as smoking prevalence. Subsequently, these PM_2.5 data were analyzed with respect to county-level adult life expectancy data for the period 2010 to 2017. Linear regression was used to determine the relationship between PM_2.5 and life expectancy in adults. Residents residing in the counties characterized as containing higher levels of PM_2.5 exhibited significantly reduced life expectancy after controlling for potential confounders. For each 10 ug/m³ increase in PM_2.5 there was an estimated mean decrease in life expectancy in adults of 0.3 years. The results of this study shed light on the relationship between fine particulate air pollution exposure and risk to human health in Taiwan.

Inhibitory effects of compounds isolated from Dioscorea batatas Decne peel on particulate matter-induced pulmonary injury in mice

Particulate matter 2.5 (PM_2.5), with an aerodynamic diameter of ≤2.5 μm, is the primary air pollutant that plays a key role associated with lung injury produced by loss of vascular barrier integrity. Dioscorea batatas Decne (Chinese yam), a perennial plant belonging to Dioscoreaceae family, is widely cultivated in tropical and subtropical regions across Asia. Both aerial parts and root of D. batatas are consumed for nutritional and medicinal purposes. The aim of this study was to (1) identify the bioactive compounds present in D. batatas peel which may be responsible for inhibition of PM_2.5-induced pulmonary inflammation in mice and (2) examine in vitro mechanisms underlying the observed effects of these compounds on mouse lung microvascular endothelial cells. The measured parameters include permeability, leukocyte migration, proinflammatory protein activation, reactive oxygen species (ROS) generation, and histology. Two phenanthrene compounds, 2,7-dihydroxy-4,6-dimethoxyphenanthrene (1) and 6,7-dihydroxy-2,4-dimethoxyphenanthrene (2) were isolated from D. batatas peels. Both these phenanthrene compounds exhibited significant scavenging activity against PM_2.5-induced ROS and inhibited ROS-induced activation of p38 mitogen-activated protein kinase. In addition, enhancement of Akt pathway, involved in the maintenance of endothelial integrity, was noted. These phenanthrene compounds also reduced vascular protein leakage, leukocyte infiltration, and proinflammatory cytokine release in the bronchoalveolar lavage fluid obtained from PM_2.5-induced lung tissues. Evidence thus indicates that phenanthrene compounds derived from D. batatas may exhibit protective effects against PM_2.5-induced inflammatory lung injury and vascular hyperpermeability in mice.

First Principles Simulations of Phenol and Methanol Detector Based on Pristine Graphene Nanosheet and Armchair Graphene Nanoribbons

Over the last decade graphene based electronic devices have attracted the interest of researchers due to their exceptional chemical, electrical and optical properties. Graphene is very sensitive to any physical changes in its surrounding environment and, inherently, has very low electronic noise. This property of graphene makes it a suitable candidate for sensor applications. The purpose of the work presented in this article is to demonstrate the ability of graphene derivatives to detect toxic organic compounds like phenol and methanol. A novel method for the detection of organic compounds (phenol and methanol) has been introduced in this article. In this method, a change in the photocurrent, as well as electric current, have been used as detection signals to improve the sensor accuracy and selectivity for specific target molecules. A nanoscale electronic device simulator, Quantumwise Atomistix Toolkit (ATK), has been used to simulate graphene nanosheet and armchair graphene nanoribbon based sensors. Devices density of states (DOS), current–voltage curves and photocurrent curves have been calculated with the ATK simulator. In the proximity of target molecules, a significant change in DOS, electric current and photocurrent have been observed. The simulated graphene based structures can be converted into physical sensors to obtain a low cost, small sized, integrated sensing device.

The impact of urbanization on air stagnation: Shenzhen as case study

One of the most concerning consequences arising from the dramatic urbanization in cities is air stagnation and the related high concentration of air pollutants. Many studies have investigated the impact of urbanization on air stagnation, but few have systematically evaluated such impact and its spatial-temporal variances at the municipal scale. This study proposed an approach based on high-resolution urban climate simulations for evaluating the impact of urbanization on air stagnation. We took the city of Shenzhen in south-eastern China, a city that grew from a small fishing and farming village to a highly urbanized city in the past thirty years, as a compelling case study. Using the WRF/Noah LSM/SLUCM model, we simulated and evaluated the probability of 6-hourly air stagnation cases (ASCs) in 1979 and 2010 at the spatial resolution of 1-km² to demonstrate the change over a thirty-year period. Comparison results show that urbanization worsened the problem of air stagnation in Shenzhen. The number of 6-hourly ASCs has increased by 21,700 for the entire Shenzhen, and by 11.4 on average for each grid with a 1 km² size. A maximum increase of 458 ASCs in a grid was also observed.