Impacts of air pollution on human and ecosystem health, and implications for the National Emission Ceilings Directive: Insights from Italy

Integration of ecological indicators to assess a multitemporal impact of cement industries

The present study evaluated an integrated biomonitoring approach based on three different bioindicators: tree rings, lichens, and beetles in a complex environment (urban-industrial-forest). In Central Italy, four sampling sites were selected to assess the anthropogenic impact of cement plants taking into account (1) long-term exposure (1988-2020) through the analysis of trace elements in tree rings of Quercus pubescens; (2) medium-term exposure (2020-2021) through the analysis of trace elements in thalli (outermost portions) of the lichen Xanthoria parietina; (3) short-term exposure in spring 2021 through the bioaccumulation and evaluation of sample vitality in transplants of the lichen Evernia prunastri and a periodic survey of entomological biodiversity carried out during spring and summer 2021. Trace elements of industrial origin were found in tree rings, with different levels of accumulation between 1988 and 2020 and a maximum in 2012. Native thalli of the lichen X. parietina showed an overall low bioaccumulation of trace elements except for Cr, probably reflecting the influence of national lockdown measures. The transplants of E. prunastri showed a weak stress response in the industrial and urban sites, but not in the forest, and identified Tl and V as the main elements contributing to atmospheric contamination, with peaks at the industrial sites. Concerning the beetles, a significantly lower number of species was found at the Semonte industrial site.

Chemical Composition of Volatile and Extractive Organic Compounds in the Inflorescence Litter of Five Species of Woody Plants

The decomposition of plant litter, most of which is found in forests, is an important element of the global carbon cycle, as a result of which carbon enters the atmosphere in the form of not only CO2 but also volatile organic compounds (VOCs). Although the formation of litter is associated with autumn cooling, in the spring, there is a very intense fall of faded inflorescences of woody plants. This study examined the chemical composition of the litter and VOCs emitted from decaying inflorescences of four species of forest-forming trees: silver birch, European hornbeam, black alder and aspen. All litter emissions consisted of 291 VOCs, mainly terpenes actively participating in atmospheric processes. The detection of a number of typical mushroom metabolites, such as 1-octen-3-ol, known as "mushroom alcohol", and alkyl sulphides, suggests that inflorescence-derived VOCs are a mixture of components of plant and microbial origin. In methanol extracts of the fallen inflorescences of all types, 263 organic compounds were identified, the majority of which were related to carbohydrates. Their share in the extracts was 72-76%. In general, the composition of the extractive compounds indicates the easy availability of this material for assimilation by various types of destructors.

Comprehensive analysis of air pollution and the influence of meteorological factors: a case study of adiyaman province

Adıyaman, a city recently affected by an earthquake, is facing significant air pollution challenges due to both anthropogenic activities and natural events. The sources of air pollution have been investigated using meteorological variables. Elevated southerly winds, especially prominent in spring and autumn, significantly contribute to dust transport, leading to a decline in local air quality as detected by the HYSPLIT model. Furthermore, using Suomi-NPP Thermal Anomaly satellite product, it is detected and analyzed for crop burning activities. Agricultural practices, including stubble burning, contribute to the exacerbation of PM10 pollution during the summer months, particularly when coupled with winds from all directions except the north. In fall and winter months, heating is identified as the primary cause of pollution. The city center located north of the station is the dominant source of pollution throughout all seasons. The study established the connection between air pollutants and meteorological variables. Furthermore, the Spearman correlation coefficients reveal associations between PM10 and SO2, indicating moderate positive correlations under pressure conditions (r = 0.35, 0.52). Conversely, a negative correlation is observed with windspeed (r = -0.35, -0.50), and temperature also exhibits a negative correlation (r = -0.39, -0.54). During atmospheric conditions with high pressure, PM10 and SO2 concentrations are respectively 41.2% and 117.2% higher. Furthermore, pollutant concentration levels are 29.2% and 53.3% higher on days with low winds. Last, practical strategies for mitigating air pollution have been thoroughly discussed and proposed. It is imperative that decision-makers engaged in city planning and renovation give careful consideration to the profound impact of air pollution on both public health and the environment, particularly in the aftermath of a recent major earthquake.

In-depth characterization of particulate matter in a highly polluted urban environment at the foothills of Himalaya-Karakorum Region

In recent years, the rising levels of atmospheric particulate matter (PM) have an impact on the earth's system, leading to undesirable consequences on various aspects like human health, visibility, and climate. The present work is carried out over an insufficiently studied but polluted urban area of Peshawar, which lies at the foothills of the famous Himalaya and Karakorum area, Northern Pakistan. The particulate matter with an aerodynamic diameter of less than 10 µm, i.e., PM10 are collected and analyzed for mineralogical, morphological, and chemical properties. Diverse techniques were used to examine the PM10 samples, for instance, Fourier transform infrared spectroscopy, x-ray diffraction, and scanning electron microscopy along with energy-dispersive x-ray spectroscopy, proton-induced x-ray emission, and an OC/EC carbon analyzer. The 24 h average PM10 mass concentration along with standard deviation was investigated to be 586.83 ± 217.70 µg/m3, which was around 13 times greater than the permissible limit of the world health organization (45 µg/m3) and 4 times the Pakistan national environmental quality standards for ambient PM10 (150 µg/m3). Minerals such as crystalline silicate, carbonate, asbestiform minerals, sulfate, and clay minerals were found using FTIR and XRD investigations. Microscopic examination revealed particles of various shapes, including angular, flaky, rod-like, crystalline, irregular, rounded, porous, chain, spherical, and agglomeration structures. This proved that the particles had geogenic, anthropogenic, and biological origins. The average value of organic carbon, elemental carbon, and total carbon is found to be 91.56 ± 43.17, 6.72 ± 1.99, and 102.41 ± 44.90 µg/m3, respectively. Water-soluble ions K+ and OC show a substantial association (R = 0.71). Prominent sources identified using Principle component analysis (PCA) are anthropogenic, crustal, industrial, and electronic combustion. This research paper identified the potential sources of PM10, which are vital for preparing an air quality management plan in the urban environment of Peshawar.

Ambient ozone at a rural Central European site and its vertical concentration gradient close to the ground

The representativeness of ambient air quality of an in situ measurement is key in the use and correct interpretation of the measured concentration values. Though the horizontal representativeness aspect is generally not neglected in air pollution studies, a detailed, high-resolution vertical distribution of ambient air pollutant concentrations is rarely addressed. The aim of this study is twofold: (i) to explore the vertical distribution of ground-level ozone (O3) concentrations measured at four heights above the ground-namely at 2, 8, 50, and 230 m-and (ii) to examine in detail the vertical O3 concentration gradient in air columns between 2 and 8, 8 and 50, and 50 and 230 m above the ground. We use the daily mean O3 concentrations measured continuously at the Košetice station, representing the rural Central European background ambient air quality observed during 2015-2021. We use the semiparametric GAM (generalised additive model) approach (with complexity or roughness-penalised splines implementation) to analyse the data with sufficient flexibility. Our models for both O3 concentrations and O3 gradients use (additive) decomposition into annual trend and seasonality (plus an overall intercept). The seasonal and year-to-year patterns of the modelled O3 concentrations look very similar at first glance. Nevertheless, a more detailed look through O3 gradients shows that they differ substantially with respect to their seasonal and long-term dynamics. The vertical O3 concentration gradient in 2-230 m is not uniform but changes substantially with increasing height and shows by far the highest dynamics near the ground between 2 and 8 m, differing in both the seasonal and annual aspects for all the air columns inspected. We speculate that non-linear changes of both seasonal and annual components of vertical O3 gradients are due to atmospheric-terrestrial interactions and to meteorological factors, which we will explore in a future study.

Toward spatially polarized human pressure? A dynamic factor analysis of ecological stability and the role of territorial gradients in Czech Republic

In light of global change, research on ecosystem dynamics and the related environmental policies are increasingly required to face with the inherent polarization in areas with low and high human pressure. Differential levels of human pressure are hypothesized to reflect development paths toward ecological stability of local systems vis à vis socioeconomic resilience. To delineate the latent nexus between socioeconomic development paths and ecological stability of local systems, we proposed a multidimensional, diachronic analysis of 28 indicators of territorial disparities, and ecological stability in 206 homogeneous administrative units of Czech Republic over almost 30 years (1990-2018). Mixing time-invariant factors with time-varying socio-environmental attributes, a dynamic factor analysis investigated the latent relationship between ecosystem functions, environmental pressures, and the background socioeconomic characteristics of the selected spatial units. We identified four geographical gradients in Czech Republic (namely elevation, economic agglomeration, demographic structure, and soil imperviousness) at the base of territorial divides associated with the increased polarization in areas with low and high human pressure. The role of urbanization, agriculture, and loss of natural habitats reflective of rising human pressure was illustrated along the selected gradients. Finally, policy implications of the (changing) geography of ecological disturbances and local development paths in Czech Republic were briefly discussed.

A Novel Method Based on Hydrodynamic Cavitation for Improving Nitric Oxide Removal Performance of NaClO2

In the removal of nitric oxide (NO) by sodium chlorite (NaClO2), the NaClO2 concentration is usually increased, and an alkaline absorbent is added to improve the NO removal efficiency. However, this increases the cost of denitrification. This study is the first to use hydrodynamic cavitation (HC) combined with NaClO2 for wet denitrification. Under optimal experimental conditions, when 3.0 L of NaClO2 with a concentration of 1.00 mmol/L was used to treat NO (concentration: 1000 ppmv and flow rate: 1.0 L/min), 100% of nitrogen oxides (NOx) could be removed in 8.22 min. Furthermore, the NO removal efficiency remained at 100% over the next 6.92 min. Furthermore, the formation of ClO2 by NaClO2 is affected by pH. The initial NOx removal efficiency was 84.8-54.8% for initial pH = 4.00-7.00. The initial NOx removal efficiency increases as the initial pH decreases. When the initial pH was 3.50, the initial NOx removal efficiency reached 100% under the synergistic effect of HC. Therefore, this method enhances the oxidation capacity of NaClO2 through HC, realizes high-efficiency denitrification with low NaClO2 concentration (1.00 mmol/L), and has better practicability for the treatment of NOx from ships.

A machine learning approach to analyse ozone concentration in metropolitan area of Lima, Peru

The main objective of this study is to model the concentration of ozone in the winter season on air quality through machine learning algorithms, detecting its impact on population health. The study area involves four monitoring stations: Ate, San Borja, Santa Anita and Campo de Marte, all located in Metropolitan Lima during the years 2017, 2018 and 2019. Exploratory, correlational and predictive approaches are presented. The exploratory results showed that ATE is the station with the highest prevalence of ozone pollution. Likewise, in an hourly scale analysis, the pollution peaks were reported at 00:00 and 14:00. Finally, the machine learning models that showed the best predictive capacity for adjusting the ozone concentration were the linear regression and support vector machine.

Are Foliar Nutrition Status and Indicators of Oxidative Stress Associated with Tree Defoliation of Four Mediterranean Forest Species?

Mediterranean forest ecosystems in Croatia are of very high significance because of the ecological functions they provide. This region is highly sensitive to abiotic stresses such as air pollution, high sunlight, and high temperatures alongside dry periods; therefore, it is important to monitor the state of these forest ecosystems and how they respond to these stresses. This study was conducted on trees in situ and focused on the four most important forest species in the Mediterranean region in Croatia: pubescent oak (Quercus pubescens Willd.), holm oak (Quercus ilex L.), Aleppo pine (Pinus halepensis Mill.) and black pine (Pinus nigra J. F. Arnold.). Trees were selected and divided into two groups: trees with defoliation of >25% (defoliated) and trees with defoliation of ≤25% (undefoliated). Leaves and needles were collected from selected trees. Differences in chlorophyll content, hydrogen peroxide content, lipid peroxidation and enzyme activity (superoxide dismutase, catalase, ascorbate peroxidase, non-specific peroxidase), and nutrient content between the defoliated and undefoliated trees of the examined species were determined. The results showed that there were significant differences for all species between the defoliated and undefoliated trees for at least one of the examined parameters. A principal component analysis showed that the enzyme ascorbate peroxidase can be an indicator of oxidative stress caused by ozone. By using oxidative stress indicators, it is possible to determine whether the trees are under stress even before visual damage occurs.

Associating Air Pollution with Cytokinesis-Block Micronucleus Assay Parameters in Lymphocytes of the General Population in Zagreb (Croatia)

Air pollution is recognized as one of the most serious public health issues worldwide and was declared to be a leading environmental cause of cancer deaths. At the same time, the cytokinesis-block micronucleus (CBMN) assay serves as a cancer predictive method that is extensively used in human biomonitoring for populations exposed to environmental contamination. The objective of this cross-sectional study is two-fold: to evaluate genomic instability in a sample (N = 130) of healthy, general population residents from Zagreb (Croatia), chronically exposed to different levels of air pollution, and to relate them to air pollution levels in the period from 2011 to 2015. Measured frequencies of CBMN assay parameters were in agreement with the baseline data for the general population of Croatia. Air pollution exposure was based on four factors obtained from a factor analysis of all exposure data obtained for the examined period. Based on the statistical results, we did not observe a significant positive association between any of the CBMN assay parameters tested and measured air pollution parameters for designated time windows, except for benzo(a)pyrene (B[a]P) that showed significant negative association. Our results show that measured air pollution parameters are largely below the regulatory limits, except for B[a]P, and as such, they do not affect CBMN assay parameters’ frequency. Nevertheless, as air pollution is identified as a major health threat, it is necessary to conduct prospective studies investigating the effect of air pollution on genome integrity and human health.

Response of atmospheric deposition and surface water chemistry to the COVID-19 lockdown in an alpine area

The effects of the COVID-19 lockdown on deposition and surface water chemistry were investigated in an area south of the Alps. Long-term data provided by the monitoring networks revealed that the deposition of sulfur and nitrogen compounds in this area has stabilized since around 2010; in 2020, however, both concentrations and deposition were significantly below the average values of the previous decade for SO₄ and NO₃. Less evident changes were observed for NH₄ and base cation. The estimated decrease of deposition in 2020 with respect to the previous decade was on average - 54% and - 46% for SO₄ and NO₃, respectively. The lower deposition of SO₄ and NO₃ recorded in 2020 was caused by the sharp decrease of SO₂ and particularly of NO_x air concentrations mainly due to the mobility restrictions consequent to the COVID-19 lockdown. The limited effects on NH₄ deposition can be explained by the fact that NH₃ emission was not affected by the lockdown, being mainly related to agricultural activities. A widespread response to the decreased deposition of S and N compounds was observed in a group of pristine freshwater sites, with NO₃ concentrations in 2020 clearly below the long-term average. The rapid chemical recovery observed at freshwater sites in response to the sharp decrease of deposition put in evidence the high resilience potential of freshwater ecosystems in pristine regions and demonstrated the great potential of emission reduction policy in producing further substantial ameliorations of the water quality at sensitive sites.

Study on Emission Characteristics and Emission Reduction Effect for Construction Machinery under Actual Operating Conditions Using a Portable Emission Measurement System (Pems)

With the acceleration of urban construction, the pollutant emission of non-road mobile machinery such as construction machinery is becoming more and more prominent. In this paper, a portable emissions measurement system (PEMS) tested the emissions of eight different types of construction machinery under actual operating conditions and was used for idling, walking, and working under the different emission reduction techniques. The results showed that the pollutant emission of construction machinery is affected by the pollutant contribution of working conditions. According to different emission reduction techniques, the diesel oxidation catalyst (DOC) can reduce carbon monoxide (CO) by 41.6–94.8% and hydrocarbon (HC) by 92.7–95.1%, catalytic diesel particulate filter (CDPF) can reduce particulate matter (PM) by 87.1–99.5%, and selective catalytic reduction (SCR) using urea as a reducing agent can reduce nitrogen oxides (NO_x) by 60.3% to 80.5%. Copper-based SCR is better than vanadium-based SCR in NO_x reduction. In addition, the study found that when the enhanced 3DOC + CDPF emission reduction technique is used on forklifts, DOC has a “low-temperature saturation effect”, which will reduce the emission reduction effect of CO and THC. The use of Burner + DOC + CDPF emission reduction techniques and fuel injection heating process will increase CO’s emission factors by 3.2–3.5 and 4.4–6.7 times compared with the actual operating conditions.

Multi-Decadal Assessment of Soil Loss in a Mediterranean Region Characterized by Contrasting Local Climates

Soil erosion is one of the most widespread soil degradation phenomena worldwide. Mediterranean landscapes, due to some peculiar characteristics, such as fragility of soils, steep slopes, and rainfall distribution during the year, are particularly subject to this phenomenon, with severe and complex issues for agricultural production and biodiversity protection. In this paper, we present a diachronic approach to the analysis of soil loss, which aims to account for climate variability and land cover dynamics by using remote data about rainfall and land cover to guarantee sufficient observational continuity. The study area (Basilicata, Southern Italy) is characterized by different local climates and ecosystems (temperate, Csa and Csb; arid steppic, Bsk; and cold, Dsb and Dsc), and is particularly suited to represent the biogeographical complexity of the Mediterranean Italy. The well-known Revised Universal Soil Loss Equation (RUSLE) was applied by integrating information from remote sensing to carry out decadal assessments (1994, 2004, 2014, and 2021) of the annual soil loss. Changes in the rainfall regime and vegetation cover activity were derived from CHIRPS and Landsat data, respectively, to obtain updated information useful for dynamical studies. For the analyzed region, soil loss shows a slight reduction (albeit always remarkable) over the whole period, and distinct spatial patterns between lowland Bsk and Mediterranean mountain Dsb and Dsc climate areas. The most alarming fact is that most of the study area showed soil erosion rates in 2021 greater than 11 t/ha*y, which is considered by the OECD (Organization for Economic Cooperation and Development) the threshold for identifying severe erosion phenomena. A final comparison with local studies shows, on average, differences of about 5 t ha−1 y−1 (minimum 2.5 and maximum 7) with respect to the local estimates obtained with the RUSLE model. The assessment at a regional scale provided an average 9.5% of soil loss difference for the arable lands and about 10% for all cultivated areas. The spatial-temporal patterns enhance the relevance of using the cover management factor C derived from satellite data rather than land cover maps, as remote observations are able to highlight the heterogeneity in vegetation density within the same vegetation cover class, which is particularly relevant for agricultural areas. For mountain areas, the adoption of a satellite-gridded rainfall dataset allowed the detection of erosion rate fluctuations due to rainfall variability, also in the case of sparse or absent ground pluviometric stations. The use of remote data represents a precious added value to obtain a dynamic picture of the spatial-temporal variability of soil loss and new insights into the sustainability of soil use in a region whose economy is mostly based on agriculture and the exploitation of natural resources.

Modelling and investigating the impacts of climatic variables on ozone concentration in Malaysia using correlation analysis with random forest, decision tree regression, linear regression, and support vector regression

Climate change is generally known to impact ozone concentration globally. However, the intensity varies across regions and countries. Therefore, local studies are essential to accurately assess the correlation of climate change and ozone concentration in different countries. This study investigates the effects of climatic variables on ozone concentration in Malaysia in order to understand the nexus between climate change and ozone concentration. The selected data was obtained from ten (10) air monitoring stations strategically mounted in urban-industrial and residential areas with significant emissions of pollutants. Correlation analysis and four machine learning algorithms (random forest, decision tree regression, linear regression, and support vector regression) were used to analyze ozone and meteorological dataset in the study area. The analysis was carried out during the southwest monsoon due to the rise of ozone in the dry season. The results show a very strong correlation between temperature and ozone. Wind speed also exhibits a moderate to strong correlation with ozone, while relative humidity is negatively correlated. The highest correlation values were obtained at Bukit Rambai, Nilai, Jaya II Perai, Ipoh, Klang and Petaling Jaya. These locations have high industries and are well urbanized. The four machine learning algorithms exhibit high predictive performances, generally ascertaining the predictive accuracy of the climatic variables. The random forest outperformed other algorithms with a very high R² of 0.970, low RMSE of 2.737 and MAE of 1.824, followed by linear regression, support vector regression and decision tree regression, respectively. This study's outcome indicates a linkage between temperature and wind speed with ozone concentration in the study area. An increase of these variables will likely increase the ozone concentration posing threats to lives and the environment. Therefore, this study provides data-driven insights for decision-makers and other stakeholders in ensuring good air quality for sustainable cities and communities. It also serves as a guide for the government for necessary climate actions to reduce the effect of climate change on air pollution and enabling sustainable cities in accordance with the UN's SDGs 13 and 11, respectively.

An assessment of spatial distribution and atmospheric concentrations of ozone, nitrogen dioxide, sulfur dioxide, benzene, toluene, ethylbenzene, and xylenes: ozone formation potential and health risk estimation in Bolu city of Turkey

Atmospheric pollutants including ozone, nitrogen dioxide, sulfur dioxide, and BTEX (benzene, toluene, ethylbenzene, and xylenes) compounds were evaluated concerning their spatial distribution, temporal variation, and health risk factor. Bolu plateau where sampling was performed has a densely populated city center, semi-rural areas, and forested areas. Additionally, the ozone formation potentials of BTEXs were calculated, and toluene was found to be the most important compound in ground level ozone formation. The spatial distribution of BTEXs and nitrogen dioxide pollution maps showed that their concentrations were higher around the major roads and city center, while rural-forested areas were found to be rich in ozone. BTEXs and nitrogen dioxide were found to have higher atmospheric concentrations in winter. That was mostly related to the source strength and low mixing height during that season. The average toluene to benzene ratios demonstrated that there was a significant influence of traffic emissions in the region. Although there was no significant change in sulfur dioxide concentrations in the summer and winter seasons of 2017, the differences in the spatial distribution showed that seasonal sources such as domestic heating and intensive outdoor barbecue cooking were effective in the atmospheric presence of this pollutant. The lifetime cancer risk through inhalation of benzene was found to be comparable with the limit value (1 × 10^-6) recommended by USEPA. On the other hand, hazard ratios for BTEXs were found at an acceptable level for different outdoor environments (villages, roadside, and city center) for both seasons.

Environmentally vulnerable or sensitive groups exhibiting varying concerns toward air pollution can drive government response to improve air quality

Air pollution seriously threatens human health, and its consequences are particularly prevalent among environmentally vulnerable or sensitive groups. However, whether the concerns among these groups are different and how they affect air pollution governance remain unclear. Here, we extract 3.8 million haze-related posts from China’s Sina Weibo and analyze the concerns raised by these groups by constructing an air pollution notability index. The results show that protection is the key theme for women aged 20–35 years, while elderly individuals are easily influenced by haze-related product ads yet lack awareness of scientific-based protection. Concerns shared by young individuals are more effective in pressuring the government in cities that experience higher levels of pollution. Concerns shared by women are more effective in cities that experience lower levels of pollution. This study evidences the influence of the public concerns conveyed via social media on air pollution governance in China.

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Online haze concerns from environmentally vulnerable groups can drive air clean

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Government response to their concern plays the key role in improving air quality

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When PM2.5 exceeds 200 μg/m³, their concern shifts from self-protection to governance

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Elders are easily drawn by haze-related ads yet lack aware of scientific protection

A comparative investigation between particle oxidation catalyst (POC) and diesel particulate filter (DPF) coupling aftertreatment system on emission reduction of a non-road diesel engine

Non-road emission regulations are becoming increasingly rigorous, which makes it necessary for non-road engines to adopt aftertreatment systems. The commonly used aftertreatments mainly include diesel oxidation catalytic (DOC), diesel particulate filter (DPF), particle oxidation catalyst (POC), selective catalytic reduction (SCR) and ammonia purification catalyst (ASC). The purpose of this study is to investigate the effects of using an integrated system (DOC + DPF/POC + SCR + ASC) on non-road diesel engine emissions under steady-state and transient operating conditions, respectively. The major works are the comparison between POC and DPF from the viewpoint of emission reduction. The results show that both POC and DPF can effectively reduce particulate matter (PM) and nitrogen oxide (NO_X) emissions under steady-state conditions, and DPF has better purification effect than POC, especially for PM. The PM conversion rate of DPF is up to 87%, while that of POC is only 60% under the non-road steady-state test cycle (NRSC). Both NO_X and hydrocarbon (HC) conversion rates are high, exceeding 95%. The conversions of PM, NO_X, HC, and carbon monoxide (CO) of DPF in the non-road transient test cycle (NRTC) are 92.83%, 96.99%, 96.86% and 81.45%, respectively, while those of POC are 60.12%, 95.45%, 92.82% and 79.51%, respectively. Both the POC and DPF systems can meet the emission regulation limits. As a result, POC has the potential to substitute DPF in non-road engines due to its lower product and maintenance costs. We hope that the comparison study will provide useful guidance for improving the emissions performance of non-road diesel engines.

An Evaluation of Risk Ratios on Physical and Mental Health Correlations due to Increases in Ambient Nitrogen Oxide (NOx) Concentrations

Nitrogen oxides (NOx) are gaseous pollutants contributing to pollution in their primary form and are also involved in reactions forming ground-level ozone and fine particulate matter. Thus, NOx is of great interest for targeted pollution reduction because of this cascade effect. Primary emissions originate from fossil fuel combustion making NOx a common outdoor and indoor air pollutant. Numerous studies documenting the observed physical health impacts of NOx were reviewed and, where available, were summarized using risk ratios. More recently, the literature has shifted to focus on the mental health implications of NOx exposure, and a review of the current literature found five main categories of mental health-related conditions with respect to NOx exposure: common mental health disorders, sleep, anxiety, depression, and suicide. All the physical and mental health effects with available risk ratios were organized in order of increasing risk. Mental health concerns emerged as those most influenced by NOx exposure, with physical health impacts, such as asthma, only beginning to surface as the fourth highest risk. Mental health conditions occupied seven of the top ten highest risk health ailments. The results summarized in this narrative review show that there are clear positive correlations between NOx and negative physical and mental health manifestations, thus strengthening the argument in support of the reduction in ambient NOx levels.

A Smart Procedure for Assessing the Health Status of Terrestrial Habitats in Protected Areas: The Case of the Natura 2000 Ecological Network in Basilicata (Southern Italy)

Natura 2000 is the largest coordinated network of protected areas in the world, which has been established to preserve rare habitats and threatened species at the European Community level. Generally, tools for habitat quality assessment are based on the analyses of land-use/land-cover changes, thus, highlighting already overt habitat modifications. To evaluate the general quality conditions of terrestrial habitats and detect habitat degradation processes at an early stage, a direct and cost-effective procedure based on satellite imagery (Landsat data) and GIS (Geographic Information System) tools is proposed. It focuses on the detection of anomalies in vegetation matrix (stress/fragmentation), estimated for each habitat at the level of both a single protected site and local network, to identify habitat priority areas (HPA), i.e., areas needing priority interventions, and to support a rational use of resources (field surveys, recovery actions). By analyzing the statistical distributions of standardized NDVI for all the enclosed habitats (at the site or network level), the Degree of Habitat Consistency (DHC) was also defined. The index allows the assessment of the general status of a protected site/network, and the comparison of the environmental conditions of a certain habitat within a given protected site (SCI, SAC) with those belonging to the other sites of the network. The procedure was tested over the Natura 2000 network of the Basilicata region (Southern Italy), considered as a hotspot of great natural and landscape interest. An overall accuracy of ~97% was obtained, with quite low percentages of commission (~8%) and omission (~6%) errors. By examining the diachronic evolution (1985–2009) of DHC and HPA, it was possible to track progress or degradation of the analyzed areas over time and to recognize the efficaciousness/failure of past managements and interventions (e.g., controlled disturbances), providing decision-makers with a thorough understanding for setting up the most suitable mitigation/contrast measures.

Brain Drain out of the Blue: Pollution-Induced Migration in Vietnam

Air pollution is a major problem that severely affects the health of inhabitants in developing countries’ urban areas. To deal with the problem, they may consider migration to another place as an option, which can result in the loss of skillful and talented workforces. This situation is called the brain drain phenomenon. The current study employed the Bayesian mindsponge framework (BMF) on the responses of 475 urban inhabitants in Hanoi, Vietnam—one of the most polluted capital cities in the world—to examine the risk of losing talented workforces due to air pollution. Our results show that people with higher educational levels are more likely to have intentions to migrate both domestically and internationally due to air pollution. Regarding the domestic migration intention, younger people and males have a higher probability of migrating than their counterparts. Age and gender also moderate the association between educational level and international migration intention, but their reliability needs further justification. Based on these findings, we suggest that environmental stressors caused by air pollution can influence citizen displacement intention on a large scale through the personal psychological mechanism of cost-benefit judgment. Due to the risk of air pollution on human resources, building an eco-surplus culture is crucial for enhancing environmental and socio-economic resilience.

Characteristics of airborne particles retained on conifer needles across China in winter and preliminary evaluation of the capacity of trees in haze mitigation

To fully understand the characteristics of particulate matter (PM) retained on plant leaves (PMR) and the effect of vegetation on haze on a large spatial scale, we investigated needle samples collected from 78 parks and campuses in 31 cities (30 provincial cities) of China and developed a comprehensive method to characterise PMR. Both the PMR load (including water-insoluble particulate matter (WIPM), water-soluble inorganic ions (WSIS) and water-soluble organic matter (WSOM)), with a mean value of 554 ± 345 mg m^-2 leaf area, and component profiles of PMR showed obvious spatial variation across the cities. Though haze pollution levels vary greatly among the 31 cities, the PM retention capacity of needles does not depend on haze level because PMR generally reaches saturation before precipitation in winter. The water-soluble component (WSC, the sum of WSIS and WSOM) accounted for 52.3% of PMR on average, among which WSIS and WSOM contributed 21.4% and 30.9% to PMR, respectively. The dominant ions of WSIS in PMR in the cities were Ca²⁺, K⁺ and NO₃^-, indicating that raised dust, biomass combustion and traffic exhaust are significant sources of PM in China. Compared with previous reports, the particle size distributions of PMR and PM across China were consistent, with fine PM (PM_2.5) constituting a substantial proportion (43.8 ± 17.0%) of PMR. These results prove that trees can effectively remove fine particles from the air, thereby reducing human exposure to inhalable PM. We proposed a method to estimate the annual amount of PMR on Cedrus deodara, with an average value of 11.9 ± 9.6 t km^-2 canopy yr^-1 in China. Compared with the load of dust fall (atmospheric particles naturally falling on the ground, average of 138 ± 164 t km^-2 land area yr^-1 in China), we conclude that trees play a significant role in mitigating haze pollution.

Geospatial Correlation Analysis between Air Pollution Indicators and Estimated Speed of COVID-19 Diffusion in the Lombardy Region (Italy)

Background: the Lombardy region in Italy was the first area in Europe to record an outbreak of COVID-19 and one of the most affected worldwide. As this territory is strongly polluted, it was hypothesized that pollution had a role in facilitating the diffusion of the epidemic, but results are uncertain. Aim: the paper explores the effect of air pollutants in the first spread of COVID-19 in Lombardy, with a novel geomatics approach addressing the possible confounding factors, the reliability of data, the measurement of diffusion speed, and the biasing effect of the lockdown measures. Methods and results: all municipalities were assigned to one of five possible territorial classes (TC) according to land-use and socio-economic status, and they were grouped into districts of 100,000 residents. For each district, the speed of COVID-19 diffusion was estimated from the ambulance dispatches and related to indicators of mean concentration of air pollutants over 1, 6, and 12 months, grouping districts in the same TC. Significant exponential correlations were found for ammonia (NH₃) in both prevalently agricultural (R² = 0.565) and mildly urbanized (R² = 0.688) areas. Conclusions: this is the first study relating COVID-19 estimated speed of diffusion with indicators of exposure to NH₃. As NH₃ could induce oxidative stress, its role in creating a pre-existing fragility that could have facilitated SARS-CoV-2 replication and worsening of patient conditions could be speculated.

Response and Deterioration Mechanism of Bitumen under Acid Rain Erosion

Acid rain as an important environmental issue has a negative impact on bitumen performance, thereby shortening the service life of asphalt pavements. Thus, this research aims to investigate the response of bitumen to acid rain and its deterioration mechanism. For this purpose, the simulated acid rain was prepared to erode neat bitumen and short-term aged bitumen. The hydrogen ion concentration of the acid rain, and the morphological, physical, chemical, and rheological properties of the bitumen were evaluated by means of a pH meter, scanning electron microscopy, physical tests, Fourier transform infrared radiation with attenuated total reflectance, and dynamic shear rheometer. The results showed that bitumen properties were severely affected by acid rain, and the changes in bitumen properties were highly related to the erosion time, leading to a reduction in pH value by 0.2 of residual acid rain, rougher bitumen surface, and stiffer bitumen with more oxygen-containing functional groups and fewer carbonyl acid groups (around 10% decrement) after 90 days erosion. These changes contributed to two deterioration mechanisms: oxidation and dissolution of carbonyl acid. Oxidation and dissolution are, respectively, the dominant actions for neat bitumen and aged bitumen during the erosion process, which eventually leads to various responses to acid rain.

Impact of ground-level ozone on Mediterranean forest ecosystems health

Given the high ozone concentrations observed in the Mediterranean region during summer, it is crucial to extend our knowledge on the potential ozone impacts on forest health with in situ studies, especially to protect typical endemic forests of the Mediterranean basin. This study is focused on ozone measurements and exposures over the Eastern Adriatic coast and on the calculation of different O₃ metrics, i.e., accumulated exposure AOT40 (AOT40_dir, AOT40_ICP, AOT40_pheno) and stomatal O₃ fluxes with an hourly threshold of uptake (Y) to represent the detoxification capacity of trees (PODY, with Y = 0, 1, 2 nmol O₃ m^-2 s^-1) used for forest protection. Finally, we provide an assessment of the relationships between the forest response indicators and environmental variables. Passive ozone measurements and monitoring of forest health indicators, namely growth and crown defoliation, were performed for Quercus ilex, Quercus pubescens, Pinus halepensis, and Pinus nigra forests. Results showed that, for all the analysed species, ozone levels were close to reached the upper plausibility limits for passive monitoring of air quality at forest sites (100 ppb), with the highest values found on P. halepensis in the summer period. O₃ metrics based on exposure were found to be higher in pine plots than in oak plots, while the highest values of uptake-based metrics were found on P. nigra. Regarding relationships between environmental variables and forest-health response indicators, the crown defoliation was significantly correlated with the soil water content at various depth while the tree growth was correlated with the different O₃ metrics. The most important predictors affecting tree growth of Q. pubescens and Q. ilex were AOT40_pheno and AOT40_dir and POD0 for P. nigra.

Clean Production of Biofuel from Waste Cooking Oil to Reduce Emissions, Fuel Cost, and Respiratory Disease Hospitalizations

Renewable energies are cleaner forms of energy, and their use, has intensified in recent decades. Thus, this work presents a proposal for reducing the emissions, fuel cost, and respiratory disease hospitalizations using environmental cost accounting principles to produce biodiesel production from waste frying oil. In our methodology, we conducted surveys, and collected waste cooking oil samples from local households and restaurants in São Paulo city, Brazil. Then, we produced biodiesel using these samples. Data on air pollutants were collected and correlated with the number of hospitalizations for respiratory diseases and their costs. Our results indicate that 330,000 respiratory disease hospitalizations were recorded in São Paulo city between 2009 and 2018, and the total cost for the Brazilian government reached US $117 million. Improving the city air quality by switching from fossil fuels to biodiesel could reduce the annual number of hospitalizations to 9880 and cost US $3.518 million, because the amount of pollutants emitted from burning fossil fuels was positively correlated with the number of respiratory disease hospitalizations and their costs. Moreover, the emission rates of particulate matter with particles less than 10 and 2.5 µm in diameter exceeded the World Health Organization limits throughout the study period. Using the survey data, we estimated that the average monthly quantity of waste cooking oil was 9794.6 m3, which could generate 9191.2 m3 of biodiesel and produce 239,713 t CO2 of carbon credits. Environmental cost accounting revealed that it would be possible to achieve an annual profit of approximately US $300 million from the sale of excess biodiesel, carbon credits, and glycerine, and fuel acquisition savings which could improve the image of São Paulo city and quality of life of its residents. Thus, we present this as a way to reduce cost and hospitalizations, and increase the number of available hospital beds for other diseases, such as COVID-19.

Association between short-term exposure to fine particulate pollution and outpatient visits for ulcerative colitis in Beijing, China: A time-series study

Environmental factors play an important role in the development of ulcerative colitis (UC). However, only few studies have examined the effects of air pollution on UC occurrence. We conducted a time-series analysis to explore the association between short-term exposure to fine particulate matter (PM_2.5) and outpatient visits for UC in Beijing, China. In total, 84,000 outpatient visits for UC were retrieved from the Beijing Medical Claim Data for Employees between January 1, 2010 and June 30, 2012. Measurements of daily PM_2.5 concentrations were obtained from the United States Embassy air-monitoring station. A generalized additive model with quasi-Poisson link was applied to examine the association between PM_2.5 concentrations and outpatient visits for UC stratified by sex, age, and season. We found that short-term exposure to PM_2.5 was significantly associated with increased daily outpatient visits for UC at lag 0 day. A 10 μg/m³ increase in PM_2.5 concentration at lag 0 day corresponded to a 0.32% increase in outpatient visits for UC (95% confidence interval (CI), 0.05-0.58%; P = 0.019). There was a clear concentration-response association between daily outpatient visits for UC and PM_2.5 concentrations. The PM_2.5 effects were significant across all sex and season subgroups, without evidence of effect modification by sex (P = 0.942) or season (P = 0.399). The association was positive in patients younger than 65 years old but negative in those 65 years old or older, although the difference was not significant (P = 0.883). In conclusion, our study demonstrated that short-term exposure to ambient PM_2.5 was significantly associated with an increased risk of daily outpatient visits for UC, especially in younger people. Additional studies are warranted to confirm our findings.

Economic impacts of ambient ozone pollution on wood production in Italy

Worldwide, tropospheric ozone (O₃) is a potential threat to wood production, but our understanding of O₃ economic impacts on forests is still limited. To overcome this issue, we developed an approach for integrating O₃ risk modelling and economic estimates, by using the Italian forests as a case study. Results suggested a significant impact of O₃ expressed in terms of stomatal flux with an hourly threshold of uptake (Y = 1 nmol O₃ m⁻² leaf area s⁻¹ to represent the detoxification capacity of trees), i.e. POD1. In 2005, the annual POD1 averaged over Italy was 20.4 mmol m⁻² and the consequent potential damage ranged from 790.90 M€ to 2.85 B€ of capital value (i.e. 255–869 € ha⁻¹, on average) depending on the interest rate. The annual damage ranged from 31.6 to 57.1 M€ (i.e. 10–17 € ha⁻¹ per year, on average). There was also a 1.1% reduction in the profitable forest areas, i.e. with a positive Forest Expectation Value (FEV), with significant declines of the annual national wood production of firewood (− 7.5%), timber pole (− 7.4%), roundwood (− 5.0%) and paper mill (− 4.8%). Results were significantly different in the different Italian regions. We recommend our combined approach for further studies under different economic and phytoclimatic conditions.

Application of neural network to simulate the behavior of hospitalizations and their costs under the effects of various polluting gases in the city of São Paulo

This work aims to obtain an artificial neural network to simulate hospitalizations for respiratory diseases influenced by pollutant gaseous such as CO, PM₁₀, PM_2.5, NO₂, O₃, and SO₂ emitted from 2011 to 2017, in the city of São Paulo. The hospitalization costs were also be calculated. MLP and RBF neural networks have been tested by varying the number of neurons in the hidden layer and the type of equation of the output function. The following pollutants and its concentration range were collected considering the supervision of Alto Tiete station set, in several neighborhoods in the city of São Paulo, from in the period 2011 to 2017: 28-63 µg/m³ of PM_2.5, 52-110 µg/m³ of PM₁₀, 49-135 µg/m³ of O₃, 0.8-2.6 ppm CO, 41-98 µg/m³ of NO₂, and 3-16 µg/m³ of SO₂. Results showed that a RBF neural network with 6 input neurons, 13 hidden layer neurons, and 1 output neuron, using BFGS algorithm and a Gaussian function to neuronal activation, was the best fitted to the experimental datasets. So, knowing the monthly concentration of gaseous pollutions was possible to predict the hospitalization of 1464 to 3483 ± 510 patients, with costs between 570,447 and 1,357,151 ± 198,171 USD per month. This way, it is possible to use this neural network to predict the costs of hospitalizing patients for respiratory diseases and to contribute to the decision-making of how much the government should spend on health care.

Comparison of Low-Cost Particulate Matter Sensors for Indoor Air Monitoring during COVID-19 Lockdown

This study shows the results of air monitoring in high- and low-occupancy rooms using two combinations of sensors, AeroTrak8220(TSI)/OPC-N3 (AlphaSense, Great Notley, UK) and OPC-N3/PMS5003 (Plantower, Beijing, China), respectively. The tests were conducted in a flat in Warsaw during the restrictions imposed due to the COVID-19 lockdown. The results showed that OPC-N3 underestimates the PN (particle number concentration) by about 2-3 times compared to the AeroTrak8220. Subsequently, the OPC-N3 was compared with another low-cost sensor, the PMS5003. Both devices showed similar efficiency in PN estimation, whereas PM (particulate matter) concentration estimation differed significantly. Moreover, the relationship among the PM₁-PM_2.5-PM₁₀ readings obtained with the PMS5003 appeared improbably linear regarding the natural indoor conditions. The correlation of PM concentrations obtained with the PMS5003 suggests an oversimplified calculation method of PM. The studies also demonstrated that PM₁, PM_2.5, and PM₁₀ concentrations in the high- to low-occupancy rooms were about 3, 2, and 1.5 times, respectively. On the other hand, the use of an air purifier considerably reduced the PM concentrations to similar levels in both rooms. All the sensors showed that frying and toast-making were the major sources of particulate matter, about 10 times higher compared to average levels. Considerably lower particle levels were measured in the low-occupancy room.

Trends in ambient O3 concentrations at twelve sites in the Czech Republic over the past three decades: Close inspection of development

Ambient or ground-level ozone (O₃), a key player in atmospheric chemistry, has been studied extensively throughout the world in recent decades due to its harmful effects on human health and the environment. The aim of this study is to examine in detail the time patterns of O₃ in the Czech Republic, a Central European country with a long-term history of ambient air pollution. We have examined the interplay between annual trends and within-a-year seasonality in daily O₃ concentrations at twelve stations representing different environments, geographical regions and altitudes in the Czech Republic in 1993-2018. We base our analysis on a generalised additive model (GAM) framework as a modern regression approach suitable for addressing non-linear trend shapes in a formalised and unified way. In particular, we use penalised splines. The inconsistent behaviour of the stations prior to 1998, two local maxima around 2003 and 2006 and a steady increase in O₃ at all sites from 2014 to the present are the main features of our study. A seasonality O₃ pattern with a clear maximum in May-June is similar for all stations. In parallel with the O₃ concentration changes over the years, the deformation of seasonality profiles over a long period of time occurs, resulting in a shift of the peak O₃ concentrations towards later days in the year. Our statistical modelling offers a detailed view of both long-term trend and seasonality components separately. Additionally, in a model with trend*seasonality interaction, we are able to study the gradual deformation of the seasonality profile over the years. Capsule: Our analysis of daily mean O₃ concentrations at twelve Czech sites in 1993-2018 revealed a steady increase in O₃ from 2014 and deformation of the seasonality O₃ profiles over the year.

Major air pollutants seasonal variation analysis and long-range transport of PM10 in an urban environment with specific climate condition in Transylvania (Romania)

The air quality decrease, especially in urban areas, is related to local-scale conditions and to dispersion of air pollutants (regional and long-range) as well. The main objective of this study was to decipher the seasonal variation of PM10, NO, NO2, NOx, SO2, O3, and CO over a 1-year period (2017) and the possible relationships between air pollution and meteorological variables. Furthermore, trajectory cluster analysis and concentration-weighted trajectory (CWT) methods were used to assess the trajectories and the source-receptor relationship of PM10 in the Ciuc basin Transylvania, known as the "Cold Pole" of Romania. The pollutants show lower concentrations during warmer periods, especially during summer, and significantly higher concentrations were observed on heating season in winter due to seasonal variations in energy use (biomass burning) and atmospheric stability. Subsequently, in February, the highest concentration of PM10 was 132 μg/m3, which is 4 times higher than the highest recorded monthly mean. Our results indicate a negative correlation between CO/temperature (- 0.89), NOx/temperature (- 0.84) and positive between NOx/PM10 (0.95), CO/PM10 (0.9), and NOx/CO (0.98), respectively. Dominant transport pathways were identified and the results revealed that slow-moving southerly (~ 45%) and northwesterly (~ 32%) air masses represent almost 80% and mainly regional flows were discerned. During 2017, increased PM10 levels were measured at the study site when air masses arrived mostly from northwest and southeast. The CWT and polarplot models show a strong seasonal variation and significant differences were observed between weekdays and weekends, namely highest PM10 concentrations during weekends at low wind speed (2-4 m/s).

Air pollution and hospital admissions due to deep vein thrombosis (DVT) in Ahvaz, Iran

There are limited studies on the relation between short-term exposure to air pollutants and the risk of deep venous thrombosis (DVT). The aim of this study was to determine the relation between the concentration of these pollutants and the risk of hospital admissions due to DVT in Ahvaz, which is one of the world's highly polluted cities. Daily data on pollutants including O₃, NO, NO₂, SO₂, CO, PM₁₀, and PM_2.5and DVT hospital admissions were collected from2008until 2018. Quasi-Poisson regression combined with linear distributed lag models; adjusted for trend, seasonality, temperature, relative humidity, weekdays, and holidays were used to assess the relation between the daily average of air pollutants and hospital admission for DVT. The results showed that there was a significant increase in hospital admissions due to DVT in the total, men, women, and elderly populations in relation to NO and NO₂. There was also a significant increase in DVT hospital admissions in the male and ≤60 years populations related to PM₁₀; and among the female and ≤60 years old populations, related to PM_2.5. Finally, the results showed that there were significant positive associations between SO2 and CO exposure and the incidence of DVT hospital admissions among men and women, respectively. The results of this study show the possible effect of short-term exposure to air pollution on the risk of DVT. Further studies are required to investigate whether direct interventions through industry and government policy may alter the impact of specific pollutants in order to alter the incidence of DVT and other identified health complications.

The city-level precision industrial emission reduction management based on enterprise performance evaluation and path design: A case of Changzhi, China

Realizing precision management, which is of great importance in city-level emission reduction management, requires scientific identification of key enterprises and differentiated emission reduction measures. However, current studies have not considered the enterprises units, or have not proposed the emission reduction paths of them. To solve this problem, this study chooses Changzhi, an industrialized city in China as a case, and considers 54 enterprises from thermal-power, cement, coking, and iron and steel sectors. The pollution performances, including the indicators of energy intensity and emission intensities of SO₂, NO_x, and PM of the 54 enterprises are evaluated. After identifying the key enterprises, this study designs their emission reduction paths including three types of measures, and quantifies the emission reduction potential. The results show that: (1) The 54 enterprises have imbalanced pollution performances, as the values have difference of 2-4 orders of magnitude. 13, 10, and 19 enterprises are classified into level A, B, and C respectively. (2) The emission reduction paths of 24 key enterprises are designed, which can reduce 3441.21, 4507.85, and 1683.12 tons of SO₂, NO_x, and PM. This accounts for 29.4%, 21.2%, and 14.9% of the total emissions. Based on these results, this study puts forward some policy suggestions of precision management measures in Changzhi. In sum, this study provides a methodology into quantitative analysis of precision air pollutant emission reduction management at city level, and put forward some critical insights of cleaner and sustainable production of the enterprises.

Spatio-temporal variations and trends of major air pollutants in China during 2015-2018

The Chinese government, as a policy response, has continued to invest efforts and resources to implement cost-effective air pollution control technologies and stringent regulation to reduce emissions from the most contributing sectors to protect the environment and public health. The higher density of monitoring stations (> 1600) distributed across China provides a timely opportunity to use them to study in detail the national pollution trends in light of more stringent air pollution control policies. In the present study, air quality datasets comprising hourly concentrations of PM2.5, O3, NO2, and SO2 collected across 1309, 1341, 1289, and 1347 monitoring stations respectively were obtained from the National Environmental Monitoring Centre over 4 years (2015-2018) and trend analysis was performed. Results indicate that the overall annual trends for PM2.5 and SO2 were - 2.9 ± 2.7 and - 3.2 ± 3.2 μg/m3/year, while the winter trends were - 4.8 ± 5.8 and - 6.9 ± 8.4 μg/m3/year respectively across China. The daily maximum 8-h average (DMA8) ozone concentration showed a significant positive trend of 2.4 ± 4.6 μg/m3/year, which was comparatively higher in summer at 4.4 ± 9.0 μg/m3/year. On the other side, NO2 trend is not great in number (- 0.45 ± 2.0 μg/m3/year). Overall, 62.2%, 61.8%, and 20.9% of PM2.5, SO2, and NO2 monitoring stations were associated with a negative trend of ≥ - 2 μg/m3/year. For O3 DMA8 concentrations, 50.7% of the monitoring stations showed a significant positive trend of ≥ 2 μg/m3/year. In light of the Chinese government's increasing impetus on combating air pollution and climate change via new policy regulations, it is important to understand the spatio-temporal distributions and relative contributions of the spectrum of gaseous pollutants to the pollution loads as well as identify changing emission loads across sectors. The results of this study will facilitate the formulation of evidence-based air pollution reduction strategies and policies.

Ambient Air Quality as a Condition of Effective Healthcare Therapy on the Example of Selected Polish Health Resorts

This article discusses the importance of air quality for the organization and functioning of health resorts. Ten different types of resorts located in various regions of Poland were compared in terms PM10 concentration. Additionally, comparative analysis of the high-PM10 episodes was performed in three urban agglomerations located near the analyzed health resorts. The article also discusses formal, legal, and economic instruments that are the basis for legislative actions as tools for managing the air quality in the selected resorts. The analysis of the average annual concentrations in 2015–2019 did not show any exceedances of the PM10 limit value for any of the health resorts studied. High PM10 concentration values in 2018 were recorded for the number of days in exceedance of the limit value, especially in the health resorts of Uniejów, Ciechocinek, and Szczawno-Zdrój. Health resorts located in the south of Poland were identified as the most at risk in terms of the occurrence of limit value exceedances, information, and alert thresholds. It was concluded that the implementation of the so called “anti-smog” resolutions, including the development of financial support for changing the heating system to eliminate coal boilers and furnaces, is absolutely necessary for air quality improvement.

Investigation of the impacts of urban vegetation loss on the ecosystem service of air pollution mitigation in Karaj metropolis, Iran

The present study aims to investigate the relationship between reduced air pollution and ecosystem services in Karaj metropolis, Iran. To the end, the trends in the concentrations of O₃, NO₂, CO, SO₂, PM₁₀, and PM_2.5 as the main atmospheric pollutants of Karaj were studied. Five time series models of autoregressive (AR), moving average (MA), autoregressive moving average (ARMA), autoregressive integrated moving average (ARIMA), and seasonal autoregressive integrated moving average (SARIMA) were used to predict changes in air pollutant concentrations. Air pollution zoning is conducted via ArcGIS_10.3 by using spline tension interpolation method. Then, normalized difference vegetation index (NDVI) was obtained from Landsat Thematic Mapper (TM) and Operational Land Imager (OLI) images to analyze vegetation dynamics as an index of ecosystem functioning. NDVI thresholds were selected to present guidelines for qualitative and quantitative changes in green cover and were divided into five different categories. Based on the results, AR (1) and ARIMA (1,2,1) were recognized as appropriate models for predicting the concentration of air pollutants in the study area. A decrease in very dense vegetation coverage and increase in poor vegetation areas, followed by an increase in air pollution, revealed that the loss of urban green coverage and decreased ecosystem services were positively related. Furthermore, the expansion of urban lands toward the north and the west from the baseline to future condition led to great changes in the land cover and losses in vegetation along these axes, which finally resulted in increased air pollution in these areas. Thus, the results of this study can be directly used in decision-making in the area of air pollution.

Effects of Air Pollution on Human Health and Costs: Current Situation in São Paulo, Brazil

This study focused on verifying whether the emission of air pollutants in São Paulo increases the costs and number of hospitalizations for respiratory diseases in Brazil. Data on pollutant emissions, hospitalizations, and hospital costs were collected from 2008 to 2017 and correlated with air quality standards. The results showed that the concentration of particulate matter increased each year during the study period and was highly correlated with hospitalizations due to respiratory diseases. Ozone (O3) was within the quality standard throughout the study period but registered an increase in the mean and a positive correlation with hospitalizations due to respiratory diseases. The carbon monoxide (CO), sulfur dioxide (SO2), and nitrogen dioxide (NO2) levels were within the quality standards throughout the study period with a decrease in the last years studied, but showed a positive correlation with hospitalizations due to respiratory diseases. The pollutant emissions and hospitalizations due to respiratory diseases had an inverse relationship with the monthly rainfall curve for São Paulo, which indicates that rainfall tended to reduce pollutant emissions and consequently hospitalizations due to inhalation of these pollutants. Because costs are directly associated with hospitalizations, both increased during the study period—302,000 hospitalizations at an average cost of 368 USD resulted in a total cost of 111 million USD. To reduce these costs, Brazil should implement stricter policies to improve the air quality of its major cities and develop a viable alternative to diesel vehicles.

Study on environmental pollution loss measurement method of waste gas emits in Nanjing MV Industrial Park

In order to realize the effective measurement of environmental pollution loss (EPL) caused by waste gas emits from energy consumption in industrial parks, it is built a shadow price model of waste gas emits in this study on the basis of literature review and status analysis. The measurement model is applied to Nanjing MV Industrial Park by using relevant statistical data. It is found that the total environmental pollution loss of waste gas emits from energy consumption in Nanjing MV Industrial Park presents a "U" change trend, which first decreases and then increases. In terms of the composition of environmental pollution loss of waste gas emits, environmental pollution loss caused by SO₂ and NO₂ stays high, which are the main components of environmental pollution loss and would be the focus of energy conservation and emission reduction in Nanjing MV Industrial Park in the future. The research results provide an effective quantitative analysis method for local government to measure the environmental pollution loss of waste gas emits from energy consumption in industrial parks and to formulate policies for environmental pollution treatment. Graphical abstract.

Au W, Zhao W, Xia ZL. A Systematic Review and Meta-Analysis of Short-Term Ambient Ozone Exposure and COPD Hospitalizations

Chronic obstructive pulmonary disease (COPD) is the third leading cause of death globally and ozone exposure is a main cause of its disease burden. However, studies on COPD hospitalizations from short-term ambient level ozone exposure have not generated consensus results. To address the knowledge gap, comprehensive and systematic searches in several databases were conducted using specific keywords for publications up to February 14, 2020. Random-effect models were used to derive overall excess risk estimates between short-term ambient-level ozone exposure and COPD hospitalizations. The influence analyses were used to test the robustness of the results. Both meta-regression and subgroup analyses were used to explore the sources of heterogeneity and potential modifying factors. Based on the results from 26 eligible studies, the random-effect model analyses show that a 10 µg/m³ increase in maximum 8-h ozone concentration was associated with 0.84% (95% CI: 0.09%, 1.59%) higher COPD hospitalizations. The estimates were higher for warm season and multiple-day lag but lower for old populations. Results from subgroup analyses also indicate a multiple-day lag trend and bigger significant health effects during longer day intervals. Although characteristics of individual studies added modest heterogeneity to the overall estimates, the results remained robust during further analyses and exhibited no evidence of publication bias. Our systematic review and meta-analysis indicate that short-term ambient level ozone exposure was associated with increased risk of COPD hospitalizations. The significant association with multiple-day lag trend indicates that a multiple-day exposure metric should be considered for establishing ambient ozone quality and exposure standards for improvement of population health. Future investigations and meta-analysis studies should include clinical studies as well as more careful lag selection protocol.

Living Environment Quality Determinants, Including PM2.5 and PM10 Dust Pollution in the Context of Spatial Issues—The Case of Radzionków

This article discusses living environment determinants in Central and Eastern Europe. It is based on a case study of the city of Radzionków, which has 16 thousand inhabitants and is located in the Silesian agglomeration in southern Poland. Hard coal has been mined in this area for almost two hundred years, and it is the main fuel used for central heating. A total of 360 buildings, divided into groups of 60 buildings each, were investigated in the selected city. Three distinct areas were distinguished in terms of living environment quality, depending on building technical condition, heating method and location. These qualities were found to be largely determined by site-specific spatial and geophysical conditions. A significant portion of the literature was found to ignore the spatial factors mentioned in this paper, instead focusing primarily on statistical data concerning pollution. This study examines site-specific variables and presents differences in air pollution levels as examined in relation to the morphological structure of development, the degree of building modernisation and heating system types.

Toward stomatal-flux based forest protection against ozone: The MOTTLES approach

European standards for the protection of forests from ozone (O₃) are based on atmospheric exposure (AOT40) that is not always representative of O₃ effects since it is not a proxy of gas uptake through stomata (stomatal flux). MOTTLES "MOnitoring ozone injury for seTTing new critical LEvelS" is a LIFE project aimed at establishing a permanent network of forest sites based on active O₃ monitoring at remote areas at high and medium risk of O₃ injury, in order to define new standards based on stomatal flux, i.e. POD_Y (Phytotoxic Ozone Dose above a threshold Y of uptake). Based on the first year of data collected at MOTTLES sites, we describe the MOTTLES monitoring station, together with protocols and metric calculation methods. AOT40 and POD_Y, computed with different methods, are then compared and correlated with forest-health indicators (radial growth, crown defoliation, visible foliar O₃ injury). For the year 2017, the average AOT40 calculated according to the European Directive was even 5 times (on average 1.7 times) the European legislative standard for the protection of forests. When the metrics were calculated according to the European protocols (EU Directive 2008/50/EC or Modelling and Mapping Manual LTRAP Convention), the values were well correlated to those obtained on the basis of the real duration of the growing season (i.e. MOTTLES method) and were thus representative of the actual exposure/flux. AOT40 showed opposite direction relative to PODY. Visible foliar O₃ injury appeared as the best forest-health indicator for O₃ under field conditions and was more frequently detected at forest edge than inside the forest. The present work may help the set-up of further long-term forest monitoring sites dedicated to O₃ assessment in forests, especially because flux-based assessments are recommended as part of monitoring air pollution impacts on ecosystems in the revised EU National Emissions Ceilings Directive.

Development of Renewable Energy Sources in the Context of Threats Resulting from Low-Altitude Emissions in Rural Areas in Poland: A Review

The process of transformation of the Polish economy, traditionally based on coal, into an economy that uses low-carbon technologies, faces a problem associated with the diversification of energy sources, especially in rural areas. The scale of the use of conventional energy carriers in households located in rural areas in Poland has a very negative impact on the natural environment. The aim of the paper is to indicate possibilities of reducing low-altitude emissions (with emitters not exceeding 40 m in height) in rural areas in Poland, through the development of renewable energy sources. This paper provides an overview of the specific character of rural areas in Poland and the development challenges faced in these areas in the investigated scope. In order to reduce greenhouse gas emissions and improve energy efficiency, it is necessary to dynamize pro-ecological activities in agriculture and in rural areas, including the development of agricultural biogas plants, wind and photovoltaic farms. The use of renewable energy sources can be an important factor in the development and sustainable growth of rural areas in Poland.

Ozone and particle fluxes in a Mediterranean forest predicted by the AIRTREE model

Mediterranean forests are among the most threatened ecosystems by the concurrent effects of climate change and atmospheric pollution. In this work we parameterized the AIRTREE multi-layer model to predict CO₂, water, ozone, and fine particles exchanges between leaves and the atmosphere. AIRTREE consists of four different modules: (1) a canopy environmental module determines the leaf temperature and radiative fluxes at different levels from above to the bottom of the canopy; (2) a hydrological module predicts soil water flow and water availability to the plant's photosynthetic apparatus; (3) a photosynthesis module estimates the net photosynthesis and stomatal conductance, and (4) a deposition module estimates ozone and PM deposition sinks as a function of the resistances to gas diffusion in the atmosphere, and within the canopy and leaf boundary layer. We describe the AIRTREE model framework, accuracy and sensitivity by comparing modeling results against long-term continuous Eddy Covariance measurements of ozone, water, and CO₂ fluxes in a Mediterranean Holm oak forest, and we discuss potential application of AIRTREE for ozone-risk assessment in view of availability of a large observational database from ecosystems distributed worldwide.

Toxicity of Exhaust Fumes (CO, NOx) of the Compression-Ignition (Diesel) Engine with the Use of Simulation

Nowadays more and more emphasis is placed on the protection of the natural environment. Scientists notice that global warming is associated with an increase of carbon dioxide emissions, which results inter alia from the combustion of gasoline, oil, and coal. To reduce the problem of pollution from transport, the EU is introducing increasingly stringent emission standards which should correspond to sustainable conditions of the environment during the operation of motor vehicles. The emissivity value of substances, such as nitrogen oxides (NOx), hydrocarbons (HC), carbon monoxide (CO), as well as solid particles, was determined. The aim of this paper was to examine, by means of simulation in the Scilab program, the exhaust emissions generated by the 1.3 MultiJet Fiat Panda diesel engine, and in particular, carbon monoxide and nitrogen oxides (verified on the basis of laboratory tests). The Fiat Panda passenger car was selected for the test. The fuels supplied to the tested engine were diesel and FAME (fatty acid methyl esters). The Scilab program, which simulated the diesel engine operation, was the tool for analyzing the exhaust toxicity test. The combustion of biodiesel does not necessarily mean a smaller amount of exhaust emissions, as could be concluded on the basis of information contained in the subject literature. The obtained results were compared with the currently valid EURO-6 standard, for which the limit value for CO is 0.5 g/km, and for NOx − 0.08 g/km, and it can be seen that the emission of carbon monoxide did not exceed the standards in any case examined. Unfortunately, when analyzing the total emissions of nitrogen oxides, the situation was completely the opposite and the emissions were exceeded by 20–30%.