PM10 Levels Research Articles

Environmental Threat Assessment Framework for Mining Activities in Guinea: An Integrated Approach for Sustainable Development.

The present study aimed to investigate the environmental consequences of mining activities in boke bauxite mining areas and the Kerouane iron mining project in Guinea using a mixed-methods approach that combines quantitative and qualitative data. A reference matrix was used to evaluate the impact of the mining activities, classifying them as negligible, moderate, or significant. Data were collected from October 2022 to January 2023 by assessing their impact on water pollution, soil, noise, air quality, vegetation, fauna, and flora. These findings indicate concerns regarding the water pH, electrical conductivity, and turbidity in both the Boke and Kerouane regions. The soil composition analysis revealed the presence of Cr, Cu, Ni, and Zn in both the Boke and Kerouane project areas. Noise levels exceeded the guideline levels and substantial amounts of particulate matter (PM) were detected, with high levels of PM10 in mining operations. The Kerouane Iron Project resulted in the direct loss of 2929 ha of natural habitats and 466 ha of modified habitats, with the extraction of approximately 1.291 billion tons of ore anticipated over a 22-year mine lifespan. This study proposes an environmental threat assessment framework that integrates technical and human activity data to evaluate the environmental impacts of mining activities comprehensively. To promote sustainable development and minimize the negative impacts of mining, an integrated index of economic and environmental performance in the mining sector is recommended, along with collaboration between researchers and policymakers to develop effective climate-change mitigation strategies.

Varying Performance of Low-Cost Sensors During Seasonal Smog Events in Moravian-Silesian Region

Air pollution monitoring in industrial regions like Moravia-Silesia faces challenges due to complex environmental conditions. Low-cost sensors offer a promising, cost-effective alternative for supplementing data from regulatory-grade air quality monitoring stations. This study evaluates the accuracy and reliability of a prototype node containing low-cost sensors for carbon monoxide (CO) and particulate matter (PM), specifically tailored for the local conditions of the Moravian-Silesian Region during winter and spring periods. An analysis of the reference data observed during the winter evaluation period showed a strong positive correlation between PM, CO, and NO2 concentrations, attributable to common pollution sources under low ambient temperature conditions and increased local heating activity. The Sensirion SPS30 sensor exhibited high linearity during the winter period but showed a systematic positive bias in PM10 readings during Polish smog episodes, likely due to fine particles from domestic heating. Conversely, during Saharan dust storm episodes, the sensor showed a negative bias, underestimating PM10 levels due to the prevalence of coarse particles. Calibration adjustments, based on the PM1/PM10 ratio derived from Alphasense OPC-N3 data, were initially explored to reduce these biases. For the first time, this study quantifies the influence of particle size distribution on the SPS30 sensor’s response during smog episodes of varying origin, under the given local and seasonal conditions. In addition to sensor evaluation, we analyzed the potential use of data from the Copernicus Atmospheric Monitoring Service (CAMS) as an alternative to increasing sensor complexity. Our findings suggest that, with appropriate calibration, selected low-cost sensors can provide reliable data for monitoring air pollution episodes in the Moravian-Silesian Region and may also be used for future adjustments of CAMS model predictions.

Assessing the impact of the National Clean Air Programme in Uttar Pradesh's non-attainment cities: a prophet model time series analysis

BackgroundUttar Pradesh, India’s largest state, faces critical pollution levels, necessitating urgent action. The National Clean Air Programme (NCAP) targets a 40% reduction in particulate pollution by 2026. This study assesses the NCAP’s impact on 15 non-attainment cities in Uttar Pradesh using the Prophet forecasting model. MethodsMonthly data from 2016 to 2023 on AQI and PM10 concentrations were sourced from the Uttar Pradesh Pollution Control Board. Significant changes in mean AQI and PM10 levels from 2017 to 2023 were evaluated using the Friedman Test. Prophet models forecasted PM10 concentrations for 2025-26, with relative percentage changes calculated and model evaluation metrics assessed. FindingsMost cities exhibited unhealthy air quality. Jhansi had the lowest AQI (72·73) in 2023, classified as 'moderate' by WHO standards. Gorakhpur consistently showed 'poor' AQI levels, peaking at 249·31 in 2019. Western Uttar Pradesh cities such as Ghaziabad, Noida, and Moradabad had significant pollution burdens. Predictions showed Bareilly with over a 70% reduction in PM10 levels, Raebareli 58%, Moradabad 55%, Ghaziabad 48%, Agra around 41%, and Varanasi 40%, meeting NCAP targets. However, Gorakhpur and Prayagraj predicted increases in PM10 levels by 50% and 32%, respectively. Moradabad’s model showed the best performance with an R2 of 0·81, MAE of 17·27 μg/m3, and MAPE of 0·10. InterpretationForecasting PM10 concentrations in Uttar Pradesh's non-attainment cities offers policymakers substantial evidence to enhance current efforts. While existing measures are in place, our findings suggest that intensified provisions may be necessary for cities predicted to fall short of meeting program targets. The Prophet model's forecasts can pinpoint these at-risk areas, allowing for targeted interventions and regional adjustments to strategies. This approach will help promote sustainable development customized to each city's specific needs. FundingNo funding was issued for this research.

Characterization of Airborne Microbial Communities in Northern Thailand: Impacts of Smoke Haze Versus Non-Haze Conditions.

Data on airborne microorganisms, particularly in Southeast Asia, are more limited compared to chemical data. This study is the first to examine the community and diversity of microorganisms on PM2.5 in an urban area of Northern Thailand during both smoke haze and non-smoke haze periods of 2020. This study evaluated the composition of airborne bacteria and fungi and analyzed their association with the chemical composition of PM2.5 and meteorological variables. Significantly higher concentrations of PM2.5 and more chemical compounds were observed during the smoke haze period compared to the non-smoke haze period. Increased PM2.5 concentrations significantly altered both bacterial and fungal communities. The diversity and richness of airborne bacteria increased, whereas those of fungi decreased. The level of PM2.5 concentration (the carrier), the chemical composition of PM2.5 (the resources for survival), and the local meteorological conditions (relative humidity (RH)) were associated with the differences in bacterial and fungal populations. In addition, air originating from the west of the receptor site, influenced by both terrestrial and marine air mass routes, contributed to higher bacterial diversity and richness during the smoke haze period. In contrast, fungal diversity and richness were greater when the air came from the southwest, following a marine route. However, the primary health concern is pathogens, which were present in both periods (such as Clostridium, Aspergillus, and Cladosporium) and were especially abundant during smoke haze periods. This study highlights those airborne microorganisms, along with the particles and their chemical composition, are important components that can impact health, including that of humans, animals, and the environment.

Seasonal Characteristics of Particulate Matter by Pollution Source Type and Urban Forest Type

To provide consistent air purification benefits from urban forests, it is crucial to identify common characteristics that allow for similar experimental setups. This study aimed to analyze PM10 concentrations in urban forests near pollution sources and understand their mitigation effects. Data from the Asian Initiative for Clean Air Networks, Korea, were used, focusing on three urban forests adjacent to road and industrial pollution sources in Korea, with PM10 concentrations collected during 2021. Considering high PM10 concentrations during winter and spring, these seasons were divided into two sub-periods, resulting in six seasonal periods for analysis. To address the right-skewed PM10 distribution and reduce outlier influence, the Kruskal–Wallis test was used. The results showed that “good” PM10 levels were lowest in early spring, increasing to a peak in summer before declining. High PM10 events were concentrated in spring, early spring, and early winter. The Kruskal–Wallis test indicated lower median PM10 concentrations in urban forests compared to pollution sources in the latter half of the year, while no significant median differences were found in the first half. Distribution visualizations further confirmed that even during high PM10 periods, all urban forests showed lower PM10 values compared to pollution sources. In conclusion, PM10 concentrations in urban forests were consistently lower than in pollution sources across all seasons, demonstrating their effectiveness in air purification at both road and industrial pollution sources. Future research should consider additional variables, such as PM2.5, to further explore differences between pollution sources.

The Prospects of Controlling Open Burning of Crop Residues in Thailand: A Quantitative Assessment of Implementation Barriers and Costs

The open burning of agricultural crop residues poses a sizable threat to Southeast Asia’s near-term prosperity and long-term sustainability. Though Southeast Asia’s policymakers have adopted burning bans and other solutions to curb this threat, few studies have systematically assessed their implementation prospects. This study offers a novel data-driven assessment of those prospects in Thailand. More concretely, it estimates how much economic, technological, institutional, and social barriers could slow the implementation of burning restrictions featured in Thailand’s PM2.5 control plan. This study finds that institutional/social barriers delay implementation more than technical/economic barriers, resulting in about twice the level of PM2.5 emissions relative to an effectively implemented policy scenario over a 10- to 20-year period. This study also demonstrates that the costs of overcoming social/institutional barriers are approximately 14 million US dollars annually over a ten-year period. This figure is equivalent to about a 70% increase on the 21 million US dollars planned for controlling burning in 2026 in Thailand. The approach employed in this study—though not free of imperfections—can also be used for finer-grained comparison of the barriers/costs of managing different crop residues in Thailand and beyond.

Ambient particulate matter and frequency of outpatient visits for chronic rhinosinusitis in the United States.

Emerging evidence has underscored the harmful effects of air pollution on the upper airway. We investigated the relationship between ambient particulate matter (PM) level and the frequency of outpatient visits for chronic rhinosinusitis (CRS). We conducted an ecological cohort study of US adults enrolled in The Merative MarketScan outpatient database from 2007 to 2020. For each geographical subunit (core-based statistical area [CBSA]), we calculated the annual rate of CRS-related outpatient visits per 1000 well-patient checkup visits (CRS-OV). Using data from the Environmental Protection Agency's Air Quality System, we mapped the rolling statistical average of daily PM2.5 and PM10 over the preceding year onto each CBSA×year combination. We employed multivariable negative binomial regression modeling to estimate the association between PM levels and subsequent CRS-OV. Across 3933 observations (CBSA×year combinations), encompassing ∼4 billion visits, the median CRS-OV was 164 (interquartile range 110-267). The mean PM2.5 level was 8.9µg/m3 (SD 2.6) and the mean PM10 level was 20.2µg/m3 (SD 7.2). Adjusting for patient demographics and respiratory comorbidities, a compounded rise in subsequent CRS-OV was observed with increasing PM levels. Each µg/m3 rise in PM2.5 independently predicted a 10% increase in CRS-OV (adjusted incidence rate ratio [aIRR]) 1.10, 95% confidence interval [CI] 1.08-1.13) and each µg/m3 rise in PM10 independently predicted a 3% increase in CRS-OV (aIRR 1.03, 95% CI 1.02-1.04). Elevated ambient PM2.5 and PM10 levels are associated with a subsequent compounded increase in the frequency of CRS-OV, with PM2.5 predicting a more pronounced rise compared to PM10.

Assessment of Indoor Air Quality and Influential Factors: A Study in Rural Areas of Solan District, Himachal Pradesh (India)

The study was conducted during December, 2020 to June, 2021 to assess indoor air quality (IAQ) and develop amelioration strategies in rural areas of the Solan district, located in Himachal Pradesh, India. A well-structured pre-tested questionnaire was used to assess the factors responsible for indoor air quality.The indoor air quality parameters including PM10, Non-Respirable Suspended Particulate Matter (NRSPM), Total Suspended Particulate Matter (TSPM), Nitrogen dioxide (NO2) and Sulfur dioxide (SO2)were studied to calculate air quality index.The findings revealed substantial variation in pollution levels among different villages. Nauni village had the highest concentration of pollutants, with PM10 levels at 24.17 µg m3-1, NRSPM at 20.37 µg m3-1, TSPM at 44.54 µg m3-1, NO2 at 12.54 µg m3-1 and SO2 at 0.35 µg m3-1. In contrast, Nagali village has the lowest levels of these contaminants. Despite variations, all recorded values were within permissible limits. Nine factors were identified as contributing to poor indoor air quality: fuel wood-based cooking, smoke sources, mode of ventilation, insect/pest control measures, waste disposal near the house, use of perfumes and air freshners, cowshed near the house, intermittent cleaning, and dampness in the house due to leakage. To reduce indoor air pollution in rural areas, the study suggests establishing concentrated methods that address these specific issues. Proper ventilation, alternate cooking methods and better waste management procedures are important steps in improving indoor air quality and protecting public health.

Elemental composition and health risk assessment of PM10, PM2.5, at different microenvironments: Addis Ababa, Ethiopia.

This study was designed to evaluate the health risks faced by inhabitants living in the slum areas of Addis Ababa, Ethiopia. The levels of PM2.5 and PM10 and elemental composition of the PM10 were measured in indoors (in the kitchen and living room) and outdoors (at the roadside). A total of 75 sampling locations (45 indoor and 30 outdoor) were selected for the study. The levels of PM2.5 and PM10 were determined using an AROCET531S instrument, while an universal air pump was used for the sampling of PM10 for the determination of trace elements by inductively coupled plasma-optical emission spectroscopy (ICP‒OES). The health impacts of PMs on the inhabitants of twelve microenvironments (MEs), where they spend much of their daily time, were estimated. The total amounts of PM2.5 and PM10, and trace metals in PM10 found in the nine or twelve MEs ranged from 10.6-119, 128-185, and 0.007-0.197 μg m-3, respectively. According to the United States Environment Protection Agency (USEPA) guidelines, ten of the twelve MEs can cause significant health problems for inhabitants (HI > 1) due to PM2.5 and PM10. Thus, special attention should be given by stakeholders/inhabitants to minimize the health impacts on long-term exposure. This study assessed the risk of levels of trace elements on the inhabitants who spend most of their daily lives. The study revealed that the lifetime cancer risk values for the individual and cumulative trace elements were within the tolerable range set by the USEPA guidelines.

Long-term effects of air pollution on daily outpatient visits for allergic conjunctivitis from 2013 to 2020: a time-series study in Urumqi, China.

This study aimed to elucidate the effects of outdoor air pollution and allergic conjunctivitis and population-based lagged effects of air pollution. We included data on six major air pollutants, PM10, PM2.5, carbon monoxide (CO), sulfur dioxide (SO2), nitrogen dioxide (NO2), and ozone (O3), and 3325 allergic conjunctivitis outpatient visits in Urumqi, northwest China, from 1 January 2013 to 31 December 2020. We developed quasi-Poisson generalized linear regression models with distributed lagged nonlinear models (DLNM), and single and multi-pollutant models were constructed to investigate single-day and cumulative lagged effects in detail. Our results confirmed that elevated PM10 and NO2 levels are significantly associated with increased allergic conjunctivitis outpatient visits with lags of 2 and 3 days respectively, and subgroup analyses further suggest that the effects of PM10 and NO2 on allergic conjunctivitis are more pronounced during the warm season. Women are more sensitive to PM10 exposure and the effect of air pollution on allergic conjunctivitis is influenced by age (e.g., infancy and older people). Our work provides the first time-series study in Urumqi, the world's furthest inland city from the ocean. Further implementation of specific outdoor air pollution controls such as the burning of fossil fuels like coal, as well as special population protection policies remain necessary. Multicenter studies with larger sample sizes are needed.

Spatial and temporal patterns of urban air pollution in tehran with a focus on PM2.5 and associated pollutants

Understanding the spatial and temporal dynamics of air pollutants is crucial for effective urban air pollution management. This study focuses on the temporal dynamics of air quality monitoring stations (AQMSs) and the association among air pollutants, particularly PM2.5, in Tehran, Iran. Using time series clustering and the Copula model, we analyzed data from 2019 to 2022. We found that the levels and dynamics of O3 and SO2 were similar across most AQMSs and unrelated to geographical positions. CO levels and dynamics were consistent among urban and border AQMSs, with higher concentrations in urban stations. NO2 levels and dynamics varied significantly among northern AQMSs with no relationship geographical positions. PM10 levels and dynamics had a relationship with geographical positions, with western clusters having the highest and northern clusters the lowest concentrations. The dynamics of PM2.5 showed significant relationship among AQMSs in the eastern, southern, and western regions, but not in the north. We also observed that PM10 and O3 levels were higher in warm seasons, whereas CO, SO2, NO2, and PM2.5 levels were higher in cold seasons. Most pollutants, except O3, peaked during traffic hours. Notably, the significant increase in PM2.5 since spring 2021 was primarily due to PM10. Policymakers should focus on these spatial and temporal variations to improve urban air quality and public health outcomes through targeted interventions.

The Formaldehyde, TVOCs, PM2.5 and PM10 Concentrations at Outdoor Street Food in Kalasin, Thailand

Human health and well-being are directly impacted by air quality. Cardiovascular and respiratory problems have been linked to exposure to pollutants such as formaldehyde, total volatile organic compounds (TVOCs), and particulate matter 2.5 and 10 micrometers (PM2.5 and PM10). This study aimed to quantify formaldehyde, TVOCs, PM2.5, and PM10 levels in the outdoor air at street food vendors in Kalasin, Thailand. The study was conducted at street food vendors in the province of Kalasin. Formaldehyde values at the top five food stalls in Kalasin ranged from 0.58 to 1.41 mg/m3. The PM2.5 values ranged from 2.29 to 9.43 ug/m3, and the TVOC values ranged from 2.91 to 7.02 ug/m3, with PM10 concentrations ranging from 2.86 to 7.29 ug/m3. Drawing on data about these pollutant concentrations across five distinct locations, the following recommendations can be put forth: Elevated levels of formaldehyde, TVOCs, PM2.5, and PM10 in certain areas can have detrimental effects on the environment and human well-being.

The Effect of PM10 Pollutant Levels on the Postneonatal Mortality Rate: Application of the AirQ+ Model in Istanbul, Türkiye.

Air pollution is one of the major environmental risk factors for health. Children are vulnerable to the negative health consequences of air pollution. We aimed to determine the effect of PM10 levels on postneonatal mortality in Istanbul, the most populous city in Türkiye. In this cross-sectional study, the relationship between PM10 levels and postneonatal deaths occurring in Istanbul, Türkiye in 2015-2019 was examined. PM10 levels for Istanbul were calculated by taking the average of daily PM10 measurements between 01.01.2015 and 31.12.2019, made available from Istanbul Air Quality Monitoring Stations. Data were analyzed using Microsoft Office Excel 2016 and AIRQ+ 2.2.3 software. If the PM10 value in Istanbul province had been reduced to 20 μg/m3, the limit value recommended by the WHO; in 2019; 36(19-61) postneonatal infant deaths could have been prevented; 7.73% (3.98-12.95) of postneonatal infant deaths were attributed to PM10. During this period, the PM10 value in Istanbul was above the limit value recommended by WHO, the European Union and Turkish legislation. Infant mortality due to air pollution is an important public health problem.

Estimating the burden of diseases attributed to PM2.5 using the AirQ + software in Mashhad during 2016–2021

The study used the AirQ + software developed by the World Health Organization (WHO) to evaluate the health impacts associated with long-term exposure to PM2.5 in Mashhad, Iran. For this purpose, we analyzed the daily average concentrations of PM2.5 (with a diameter of 2.5 micrometers or less) registered by the air quality monitoring stations from 2016 to 2021. The levels of PM2.5 surpassed the Air Quality Guidelines (AQG) limit value of 5 µg/m3 (annual value) established by WHO. The findings revealed that the burden of mortality (from all-natural causes) at people above 30 years old associated with PM2.5 exposures was 2093 [95% confidence interval [CI]: 1627–2314] deaths in 2016 and 2750 [95% CI: 2139–3038] deaths in 2021. In general, the attributable mortality from specific causes of deaths (e.g., COPD (chronic obstructive pulmonary diseases), IHD (ischemic heart diseases) and stroke) in people above 25 years old increased between the years, but the mortality from lung cancer was stable at 46 [95% CI: 33–59] deaths in 2016 and 48 [95% CI: 34–61] deaths in 2021. The attributable mortality from ALRI (Acute Lower Respiratory Infection) in children below 5 years old increased between the years. We also found differences in mortality cases from IHD and stroke among the age groups and between the years 2016 and 2021. It was concluded that burden of disease methodologies are suitable tools for regional and national policymakers, who must take decisions to prevent and to control air pollution and to analyze the cost-effectiveness of interventions.

Age trend in the mortality from diseases of the circulatory system during the pandemic under a decrease in air pollution

Introduction. The results of large-scale studies of the mortality from diseases of the circulatory system (DCS) during the pandemic require further analysis of the data and the search for modifying factors. The purpose is to identify the features of the trend in the mortality from DCS in the population of an industrial center during a pandemic under changes in air pollution. Materials and methods. The research was carried out in the industrial center – Bratsk. Age-specific mortality rates were studied using exponential models in the background (2017) and pandemic (2021) periods. The contribution of atmospheric air pollution to the mortality rate was calculated in accordance with the “Guidelines for assessing the risk to public health from exposure to chemical substances that pollute the environment.” Results. The age-related increase in the mortality rate from DCS over 2017 was 125%, and during 2021 – 172%. During the pandemic, the excess mortality rate was in cases older 80 years – 35.92‰, 70–79 – 8.48‰, 60–69 – 1.03‰. PM10 levels in the air decreased from high to alarming levels in 2021, resulting in a reduction in excess PM10-related deaths from 194 (CI: 193.6–195.1) to 5.0 (CI: 4.8–5.1) cases. Limitations are associated with incomplete epidemiological knowledge about the dependence of mortality from DCS on exposure to air pollutants. Conclusion. The use of nonlinear regression analysis made it possible to demonstrate changes in trends in age-specific mortality during the background period and during the pandemic. During the pandemic, the level of excess mortality was revealed to relate with PM10 air pollution decreased.

Classroom indoor air quality and noise level assessment of different educational institutions in a university area in Bangladesh

Introduction: The classroom environment is crucial for fostering effective learning and safeguarding teacher-student health. This study assessed the Indoor Air Quality (IAQ) and noise levels in classrooms across three institutions: a university, a secondary and higher secondary school (called a school and college), and a primary school. Materials and methods: Various IAQ parameters such as Particulate Matters (PM2.5 and PM10), Carbon monoxide (CO), Carbon dioxide (CO2), Total Volatile Organic Compound (TVOC), and temperature, Relative Humidity (RH), light, and noise levels were measured using calibrated instruments from February to March 2024. Results: The air pollutants and noise levels varied among the institutions. The mean values of PM 2.5 (76.6 µg/m3) and PM (116.7 µg/m3) were highest The mean values of PM 2.5 (76.6 µg/m3) and PM (116.7 µg/m3) were highest in the primary school, while CO (0.82 ppm), light (92.9 lux), temperature (27.6 °C), and noise levels (77.6 dB) peaked in the school and college. University classrooms showed the maximum concentrations of CO2 (804.9 ppm), TVOC (32.9 ppb), and RH (58.6%). In all institutions, PM2.5, PM10, and noise levels exceeded WHO-recommended limits, whereas CO, CO2, RH, and temperature remained within their respective standards. Light levels were below Occupational Safety and Health Administration (OSHA) guidelines. Correlation analysis showed significant positive correlations between PM2.5 PM10, and CO. Hazard Quotient (HQ) values for PM 2.5 and PM10 exceeded 1.0, indicating potential health risks. Variations in pollutants and noise levels among institutions may be due to classroom facilities, student density, ventilation systems, and student activities. Conclusion: Long-term exposure to IAQ pollutants and noise levels could impair cognitive function, respiratory health, and overall well-being of the students and educators. Implementing proper ventilation (e.g., HEPA filters) systems, soundproofing acoustic panels, and continuous IAQ monitoring is recommended for a safer classroom environment.

Accumulation of heavy metals in the leaves of different tree species and its association with the levels of atmospheric PM2.5-bond heavy metals in Isfahan

This study aimed to biomonitor air pollution by measuring heavy metals (HMs) accumulation levels in the leaves of common urban trees, Cupressus arizonica Greene, Melia azedarach L., Morus alba L. and Buxus colchica in different regions of Isfahan. Their association with the levels of PM2.5 and PM2.5-bond HMs was also investigated. PM2.5 were collected on a glass-fiber filter and measured by gravimetric method. The HM contents of the PM2.5 and tree leaves were extracted and analyzed by ICP-OES. The average PM2.5 concentrations in ambient air of all areas varied from 52.34 to 103.96 μg/m3. The mean HMs levels in the leaves were in the following orderZn(31.2) > Cu(11.04) > Pb(4.38) > Ni(4.01) > Cr(3.03) > Co(0.61) > Cd(0.04) (μg/g). The highest level of HMs was detected in the leaves of Morus alba L., followed by Buxus colchica, Melia azedarach L. and Cupressus arizonica Greene. There was a significant correlation between the amounts of Pb and Cu in tree leaves and those in ambient PM2.5 (p value ≤ 0.05). In conclusion, tree leaves can be used as a suitable bioindicator in the evaluation of air pollution. Morus alba L. compared to the other species can be confidently used for green space development.

Causes of the unremitting high ambient levels of PM10 in a suburban background site in NE Spain

Atmospheric PM10 and benzo(a)pyrene (BaP) concentrations in Manlleu (NE Spain) have remained high from 2008 to 2023, frequently exceeding EU limit/target values, and reaching BaP levels up to six times higher than urban averages in Spain. Furthermore, PM speciation campaigns were carried out in 2013, 2014–2015, 2016–2017 and 2021–2022. Chemical mass closure for autumn-winter showed a consistent PM10 composition for the different PM speciation campaigns, comprising 46–53% organic matter (OM), 18–26% secondary inorganic aerosol (SIA), 13–23% mineral matter (MM), and 5–9% elemental carbon (EC). Trend analysis revealed very light decrease and constant concentrations for PM10 and BaP, respectively over the study period, emphasizing the need for compliance with current and forthcoming EU air quality directives, the last aiming to halve PM10 limit values. Source apportionment of samples of the sporadic campaigns identified biomass burning (BB, 17.5 μg m−3, 48%) and MM and industry (16.3 μg m−3, 44%) as the main autumn-winter PM10 contributors, with high SIA concentrations attributed to several factors, including high ammonia (NH3) emissions. Local topography and meteorological conditions contribute to aggravate PM10 pollution. While metal concentrations have decreased since 2013, suggesting reduced industrial emissions, persistently high OM and EC concentrations indicate ongoing issues with BB emissions from domestic, commercial, and agricultural sources. Online analysis of black carbon (BC) and non-refractory PM1 components during winter 2016–2017 confirmed domestic and commercial BB as the primary sources of the BB contributions. These findings highlight the need of the implementation of more effective measures in reducing BB and agricultural/farming NH3 emissions. This study highlights the relevance of these issues for similar towns, the probable unremitting problem over the last decade, and the necessity of enhanced monitoring in small cities and policy actions to meet air quality standards under the new EU directive.

The complex chemical effects of air pollutants, meteorology and dust on the concentrations of criteria and non-criteria air pollution in Kuwait

Air pollution is the leading environmental health risk factor globally. A number of cities experienced improvements in air quality during the COVID-19 lockdown; however such changes depend on the contributions from natural and anthropogenic sources and meteorological factors pertaining to each city. This study investigated the effects of anthropogenic and meteorological factors on air quality in Kuwait during the COVID-19 lockdown (22 March–10 May 2020) using mixed-effect regression and machine learning models. Criteria (PM2.5, PM10, NO2, O3, SO2, CO) and non-criteria (C6H6, NH3, H2S, NMHC) air pollutants were compared between the lockdown period, and the same period in the preceding and the following years, 2019 and 2021, respectively. The results showed that during the lockdown three criteria air pollutants (PM2.5, NO2, CO) were reduced by 38, 40, 26%, respectively. All no-criteria air pollutants were reduced, except for H2S. The arid region’s harsh desert conditions have major contributions to particulate pollution. Although PM levels are overwhelmed by meteorological and natural dust, stringent abatement measures on oil/gas hydrocarbon and power plant emissions can significantly reduce PM and other pollutants. Abatement measures on traffic pollution can further reduce the NO2 levels. This study highlights Kuwait's ongoing struggle with elevated levels of particulate and gaseous pollution, driven by hydrocarbon emissions and dust. Effectively tackling air quality requires a nuanced understanding of the interplay between air pollutants, meteorological, and dust covariates.

Cost benefit analysis of reducing speed limits in Athens to 30 Km/h

The objective of this research is to investigate public acceptance and socio-economic feasibility of reducing speed limit from 50 km/h to 30 km/h in certain parts of the road network of Athens, Greece. A questionnaire was developed based on the method of stated preference for various hypothetical scenarios of time, fuel consumption and the probability of road crash to investigate road user preferences towards the reduction of speed limit and identify the most important influencing factors preferences. A total of 408 respondents were asked to choose among three alternative proposals: a) Reduce the speed limit to 30 km/h throughout the urban network except on major arteries, b) Reduce the speed limit to 30 km/h throughout the urban network and c) No Reduction (do nothing). For the analysis, two binomial logistic regression models and two multinomial logistic regression models were developed. The results indicate that increase in travel time, the importance of speed in causing a crash, the number of crashes the user has been involved in, the respondent’s driving habits are the main determinants of the users’ preferences. Furthermore, a Cost Benefit Analysis (CBA) was conducted to understand the sustainability implications of the implementation of lower speed limits (i.e., 50 to 30 km/h). In terms of socio-economic impacts, the CBA considered safety-related metrics, namely the number of road casualties of all severity levels, and environmental-related metrics, namely reductions in CO2, NOx, PM levels as well as in road user surplus metrics namely travel time increase and fuel consumption reduction. Costs considered in the analysis result from increased time spent on the road. Consequently, the investment and the operational costs along with the socio-economic impact are estimated and monetized, up to the year 2030. The positive Net Present Value (NPV) and the high Internal Rate of Return (IRR), i.e. 64.5 %, obtained as well as the sensitivity analysis results, indicate the feasibility of this policy over time. Therefore, speed limit reductions are economically viable and so, should be encouraged.