Local Air Research Articles

The environmental consequences of industrial agglomeration: New evidence from city-level data in China

In the context of sustainable development, environmental policies increasingly focus on reducing carbon emissions worldwide. Industrial agglomeration (IAGG) has emerged as a potential factor in achieving this objective by reducing carbon emissions and improving air quality. This study examines the direct and indirect impacts, spatial dynamics, and policy impacts of industrial agglomeration on air pollution levels. Panel data from 278 cities in China between 2011 and 2020 are utilized to investigate the potential of industrial agglomeration to reduce air pollution. Multiple regression models are employed, these models explore the mechanisms through which industrial agglomeration can have a positive effect on air pollution, highlighting economic growth, inclusive finance, digital economy and technological innovation as crucial factors. The study also investigates the spatial spillover effects of industrial agglomeration, finding that the concentration ratio and specialization of neighbouring cities significantly contribute to local air pollution levels. Furthermore, this contribution increases progressively with distance. The study investigates the spillover effects of environmental pollution and industrial agglomeration-related policies on PM2.5 concentration, concluding that such spillover effects lead to a decrease in PM2.5 concentration in neighbouring locations.

Quantifying the impact of urban trees on air quality in Geneva, Switzerland

Atmospheric pollution threatens human health worldwide, with tropospheric ozone (O3) and particulate matter (PM) among the most harmful pollutants. Urban trees can reduce the concentration of air pollutants through dry deposition on their canopies and stomatal uptake. At the same time, urban trees can deteriorate air quality by emitting aerosol- and O3 precursors in the form of biogenic volatile organic compounds (BVOCs). O3 and PM removal, and BVOC emissions vary depending on the tree species. Therefore, the diversity and spatial distribution of urban trees significantly influence their impact on local air quality. This study employs a dual approach to assess and map the impact of urban trees on air quality in Geneva, Switzerland. Firstly, we use the i-Tree Eco model combined with a tree inventory (237,191 trees) to quantify BVOC emissions and PM10 (PM < 10 µm) and O3 removal at the genus level. Secondly, we develop a species-level parameterization using 51 common urban tree species to estimate the same variables and ozone-forming potential (OFP). Results show that the tree density is heterogeneous in the study area, leading to neighborhoods with greater biomass and, therefore, stronger influence by trees on local air quality. According to i-Tree Eco, urban trees in Geneva emitted 50 t of BVOCs, while removing 14 t of PM10 and 52 t of O3 in 2014. With the species-level parametrization, we estimate that urban trees removed about 66 ± 55 t of PM10 and 150 ± 96 t of O3 in 2014. However, they could also emit about 130 ± 52 t of BVOCs annually, which, under favorable conditions, can form 1153 ± 519 t of O3. Depending on the method, urban trees removed between 4 and 19 % of the anthropogenic PM10 emissions. The annual removal rates are comparable to findings in other European cities. The disparities between the two approaches are due to different parameterizations. This study could help urban planners to select adequate species for future planting programs in Geneva and more generally. It showed that the impact of urban trees on air quality is spatially heterogeneous but significant, and tightly linked to the species composition.

Could residential air-source heat pumps exacerbate outdoor summer overheating and winter overcooling in UK 2050s climate scenarios?

The UK government promotes heat pumps to replace gas boilers in the residential sector as a vital part of its strategy to achieve Net Zero by 2050. As climate change intensifies, heat pumps, traditionally used for heating, will also play a role in cooling to address indoor heat risks that threaten public health and increase energy demands. However, air-source heat pumps (ASHPs) might unintentionally exacerbate summer overheating and winter overcooling in residential neighbourhoods. This study uses a multi-scale modelling approach, combining SUEWS and EnergyPlus, to assess the impact of ASHPs on outdoor temperature in two idealised UK low-rise residential neighbourhoods under 2050s climate scenarios. Results show that in summer, ASHPs increase median anthropogenic heat emission by up to 19.3 W m-2 and raise local median 2 m air temperature by up to 0.12 °C in an idealised London neighbourhood. In winter, replacing gas boilers with ASHPs for heating reduces anthropogenic heat emissions by up to 11.1 W m-2 and lowers local air temperatures by up to 0.16 °C in London. The research shows that conventional waste heat calculations from air-conditioning can overestimate anthropogenic heat emissions by up to 86 %, and cooling entire building rather than just occupied rooms can increase energy consumption by 68 %. Although temperature changes will vary across UK cities, the response of air temperature to anthropogenic heat change is generally consistent. The study enhances understanding of role of ASHPs in the UK's net zero target for 2050, highlighting the importance of balancing outdoor and indoor thermal comfort when considering the wide use of ASHPs.

The role of local institutional quality for the digital and environmental transitions in Italy

In this paper we analyze the effect of institutional quality on the so-called Twin transition at provincial level in Italy. To carry out the analysis, we use two proxies for the ecological transition, namely waste management and air pollution, and two proxies for the digital transition, namely ultra-wide band connections and provincial innovative start-ups. All the models are estimated on a panel of 103 provinces with a time dimension that varies for the different dependent variables. We employ Spatial Durbin Model estimator to take into account spatial dependence across provinces. Our findings indicate that the quality of local institutions may have an important role for the ecological transition, but not for the digital transition. Higher levels of institutional quality increase the performance in waste management and reduce the level of local air pollution. Conversely, the estimated coefficient of institutional quality is not statistically significant neither for ultra-wide band nor for innovative start-ups. Institutional quality turns to be significant but negative for the digital transition when dummy variable controlling for the presence of science-oriented university is added in the model specification. These results confirm that the green transition is largely policy-driven and the local ‘institutional environment’ is an essential ingredient for its effectiveness. The driving forces of the digital transition, instead, can be better found in socio-economic factors that depend on the ‘economic quality’ of the local system and its propensity to innovate within larger-scale innovation trajectories.

Enhancing Air-Quality Predictions on University Campuses: A Machine-Learning Approach to PM2.5 Forecasting at the University of Petroșani

This study focuses on predicting PM2.5 levels at the University of Petroșani by employing advanced machine-learning techniques to analyze a dataset that encapsulates a wide array of air pollutants and meteorological factors. Utilizing data from Internet of Things (IoT) sensors and established environmental monitoring stations, the research leverages Random Forest, Gradient Boosting Machines, and Support Vector Regression models to forecast air quality, emphasizing the complex interplay between various pollutants. The models demonstrate varying degrees of accuracy, with the Random Forest model achieving the highest predictive power, indicated by an R2 score of 0.82764. Our findings highlight the significant impact of specific pollutants such as NO, NO2, and CO on PM2.5 levels, suggesting targeted mitigation strategies could enhance local air quality. Additionally, the study explores the role of temporal dynamics in pollution trends, employing time-series analysis to further refine the predictive accuracy. This research contributes to the field of environmental science by providing a nuanced understanding of air-quality fluctuations in a university setting and offering a replicable model for similar environments seeking to reduce airborne pollutants and protect public health.

The Fogees system for forecasting particulate matter concentrations in urban areas

Air quality forecasting requires appropriate models and data sources. The Fogees system presented in this paper enables mapping, evaluation and forecasting of the level of PMx pollution in the air, for urban and suburban areas. Input data were downloaded from the Meteoblue service, the GIS database and – in the case of integration with existing measurement systems – also from local air quality monitoring stations. The system uses a diagnostic model to determine the velocity field and a Lagrange model to describe pollution dispersion. The system has an autocalibration model and uses proprietary algorithms to estimate emissions from domestic heating, transport and background pollution levels. Modular design and parallel computation facilitate simultaneous calculation of forecasts for existing emission conditions and calculations for alternative emission conditions. The system permits forecasting for the next hour and for several consecutive hours. The validation results confirm that the system reliable forecasting of PM concentrations.

Spatio-Temporal Assessment of Air Quality in Rajsamand District, Rajasthan Using Cloud-Based Google Earth Engine Approach

This study examines the spatial and temporal variations of key air pollutants in Rajsamand District, Rajasthan, from January 2015 to December 2019, using Sentinel-5P TROPOMI data. The pollutants analysed include carbon monoxide (CO), nitrogen dioxide (NO2), formaldehyde (HCHO), sulphur dioxide (SO2), methane (CH4), and aerosols. The findings reveal significant impacts of marble mining activities on local air quality. CO levels increased notably near mining sites, with mean annual values rising from 0.022 mol/m2 in 2015 to 0.026 mol/m2 in 2019. NO2 concentrations peaked near urban and industrial areas, increasing from 0.00013 μg/m3 in 2015 to 0.00016 μg/m3 in 2019. Elevated HCHO levels were observed near mining clusters, with concentrations rising from 0.00018 μg/m3 in 2015 to 0.00021 μg/m3 in 2019, posing significant respiratory health risks. SO2 emissions, primarily from diesel machinery and blasting activities, increased from 0.00028 ppm in 2015 to 0.00031 ppm in 2019. CH4 concentrations, influenced by underground releases during mining, increased from 1795 ppm in 2015 to 1810 ppm in 2019. Aerosol levels, elevated due to dust emissions from mining, increased from 0.48 μg/m3 in 2015 to 0.51 μg/m3 in 2019. These results underscore the need for stringent air quality regulations and sustainable mining practices to mitigate environmental and health impacts in Rajsamand District.

Variations of dissolved trace elements in precipitation and stream water in Japanese forest area: additional evidence of changing air pollution in the region

Trace elements released into the atmosphere by human activities, such as fossil fuel combustion, flow into forest ecosystems via wet and dry deposition and can flow out via mountainous stream water. The Kajikawa catchment site in Niigata Prefecture, located on the Sea of Japan side in central Japan, suffers from large amounts of acidic substance deposition due to its geographical conditions and meteorological seasonality and is affected by transboundary air pollution originating from the Asian continent due to northwesterly seasonal winds in winter. This study determined the concentrations of trace elements dissolved in precipitation and stream water to comprehensively evaluate the effects of transboundary air pollution on forest ecosystems. The results showed that the concentrations of trace elements and major inorganic ions in precipitation tended to be high in winter and low in summer. The fluxes of many trace elements also increased in winter, reflecting high precipitation amount. Except for Sr, the enrichment factors of the highly enriched trace elements did not show clear seasonality. Therefore, they were continuously influenced by anthropogenic activities. Furthermore, the stable Pb isotope ratio changed significantly during the observation period; however, this was not explained by seasonal changes. This study revealed that trace elements are transported to the Sea of Japan side in central Japan, especially in winter; however, their quantity and content change in response to changes in local and transboundary air pollution.Graphical

Inter-annual variability and health risk assessment of summer VOCs in a Plain City of China

This study investigated the inter-annual variations, transport pathways, pollution sources, and health implications of volatile organic compounds (VOCs) in Zhengzhou, China, a city notably affected by ground-level ozone (O3) pollution. Analyzing VOCs data from the summers of 2017–2021 revealed an average summer VOCs concentration of 61.8 ± 18.2 μg/m3, predominantly consisting of alkanes (55.0%), aromatics (22.5%), and alkenes (16.9%). The study identified significant year-to-year disparities in VOC abundances and compositions, which were closely linked to meteorological conditions, including temperature, wind speed, and relative humidity. Additionally, factors like air mass origin, direction and transport distance critically influenced the VOCs characteristics, with local air masses exhibiting higher VOC concentrations than those from distances of 100–500 km to the northwest, west and east. Positive Matrix Factorization (PMF) analysis identified major sources of VOCs as vehicle exhaust, oil and gas evaporation, solvent use, and biogenic emissions, with their contributions varying annually influenced by regional transport, environmental policies, and the COVID-19 pandemic. Health risk assessments, following U.S. Environmental Protection Agency guidelines, indicated negligible non-carcinogenic and carcinogenic risks from VOCs exposure, except for a potential carcinogenic risk from ethylbenzene. Solvent use sources were found to have the highest risks, with non-carcinogenic risks at 4.1 × 10−3 (negligible) and carcinogenic risks at 7.8 × 10−7 (with potentially carcinogenic in 2017 but negligible in subsequent years). This research underscored the complex dynamics of VOCs pollution and provided insights for developing effective pollution control strategies and enhancing public health in urban settings.

Environmental Awareness and Walking Behavior to the Grocery Store

The relationship between environmental awareness and actionable change is complex. While extensive literature examines the links between green ideology and eco-friendly behavior, few studies focus on how green ideology influences transportation choices and the built environment. This study investigates the relationship between environmental awareness and walking behavior, addressing three research questions aimed at: identifying socio-demographic characteristics linked to a high level of environmental awareness; exploring how environmental awareness affects perceptions of walkability; and determining whether individuals committed to community environmentalism are more likely to walk to the grocery store. The findings reveal that higher income is associated with considerations of local air quality, noise, and the importance of positive environmental transportation choices. Car ownership negatively impacts the willingness to adjust routes or travel time to minimize environmental impact. Environmentally aware individuals perceive the grocery store as closer, feel safer walking, view sidewalks as more available and in a better condition, and notice more tree shading. Those who consider air quality and noise levels in their walking decisions are more likely to notice tree shading. Individuals committed to community environmentalism are significantly more likely to walk to the grocery store, underscoring the crucial role of environmental values in shaping transportation behaviors and walkability perceptions.

Machine learning framework for high-resolution air temperature downscaling using LiDAR-derived urban morphological features

Climate models lack the necessary resolution for urban climate studies, requiring computationally intensive processes to estimate high resolution air temperatures. In contrast, Data-driven approaches offer faster and more accurate air temperature downscaling. This study presents a data-driven framework for downscaling air temperature using publicly available outputs from urban climate models, specifically datasets generated by UrbClim. The proposed framework utilized morphological features extracted from LiDAR data. To extract urban morphological features, first a three-dimensional building model was created using LiDAR data and deep learning models. Then, these features were integrated with meteorological parameters such as wind, humidity, etc., to downscale air temperature using machine learning algorithms. The results demonstrated that the developed framework effectively extracted urban morphological features from LiDAR data. Deep learning algorithms played a crucial role in generating three-dimensional models for extracting the aforementioned features. Also, the evaluation of air temperature downscaling results using various machine learning models indicated that the LightGBM model had the best performance with an RMSE of 0.352 °K and MAE of 0.215 °K. Furthermore, the examination of final air temperature maps derived from downscaling showed that the developed framework successfully estimated air temperatures at higher resolutions, enabling the identification of local air temperature patterns at street level. The corresponding source codes are available on GitHub: https://github.com/FatemehCh97/Air-Temperature-Downscaling.

Physicochemical Characterization of Religious Burning Aerosols in Lhasa on the Qinghai‐Tibet Plateau

AbstractReligious burning (RB) has been identified as a major source of atmospheric aerosols on the Qinghai‐Tibet Plateau. However, there is limited understanding of the detailed chemical composition, size distribution, and optical properties of RB aerosols in this region. To characterize these important aerosol properties, ambient PM2.5 and size resolved aerosols from RB emissions in Lhasa were collected during summer 2019. Organic functional group (OFG) and inorganic ion composition was measured using Fourier transform infrared spectroscopy and ion chromatography, respectively. The ambient PM2.5 was dominated by organic components, with the OFG concentrations significantly higher during religious events, reflecting the substantial impact of RB emissions on local air quality. The RB aerosols were characterized by high fractions of alkane (34%), hydroxyl (29%), and carboxylic acid (13%) groups, with peak mass in the accumulation mode (0.56–1.00 μm). The high abundance of hydroxyl group and the size distribution pattern suggested that the RB aerosols were formed from volatilization of fuel materials followed by unaltered condensation, a process that may be unique to the low‐temperature, low‐oxygen burning in the scattered burners at the temples. The absorption coefficient of RB aerosols showed similar size distribution to the mass size distribution, but the absorption Ångström exponent displayed the lowest value in the 0.56–1.00 μm size mode. This specific size distribution aligned with the mass fraction of carboxylic acids and mirrored the mass proportion of alkanes, suggesting that smaller and larger particles were enriched with substances that have higher light‐absorbing capabilities.

International airport emissions and their impact on local air quality: chemical speciation of ambient aerosols at Madrid–Barajas Airport during the AVIATOR campaign

Abstract. Madrid–Barajas Airport (MAD) is the fourth-busiest airport in Europe. The aerosol chemical composition and the concentrations of other key pollutants were measured at the airport perimeter during October 2021 to assess the impact of airport emissions on local air quality. A high-fidelity ambient instrumentation system was deployed at Madrid–Barajas Airport to measure the following: concentrations of organic aerosols (with their composition), black carbon (eBC), carbon dioxide (CO2), carbon monoxide (CO), nitrogen dioxide (NOx), sulfur dioxide (SO2), particulate matter (PM2.5, PM10), total hydrocarbon (THC), and total particle number. The average concentrations of eBC, NOx, SO2, PM2.5, PM10, CO, and THC at the airport for the entire campaign were 1.07 µg m−3, 22.7 µg m−3, 4.10 µg m−3, 9.35 µg m−3, 16.43 µg m−3, 0.23 mg m−3, and 2.30 mg m−3, respectively. The source apportionment analysis of the non-refractory organic aerosol (OA) using positive matrix factorisation (PMF) allowed us to discriminate between different sources of pollution, namely less oxidised oxygenated organic aerosol (LO-OOA), alkane organic aerosol (AlkOA), and more oxidised oxygenated organic aerosol (MO-OOA). The results showed that LO-OOA and MO-OOA account for more than 80 % of the total organic particle mass measured near the runway. Trace gases correlate better with the AlkOA factor than LO-OOA and MO-OOA, indicating that AlkOA is mainly related to primary combustion emissions. Bivariate polar plots were used for pollutant source identification. Significantly higher concentrations of the obtained factors were observed at low wind speeds (&lt;3 m s−1) from the southwest, where two of the runways and all terminals are located. Higher SO2/NOx and CO/eBC ratios were observed when the winds originated from the northeast, where the two northern runways are located. These elevated ratios are attributed to the aircraft activity being the major pollutant source in the northeast area.

Warehouses worsen local air pollution

Warehouses worsen local air pollution

Spatial Mapping of Air Pollution Hotspots around Commercial Meat-Cooking Restaurants Using Bicycle-Based Mobile Monitoring

Mobile measurement techniques are increasingly utilized to monitor urban emissions, regional air quality, and air pollutant exposure assessments. This study employed a bicycle measurement method to obtain the detailed distribution of air pollutant concentrations in roadside, commercial, residential, and recreational areas. The study area is located in Chuncheon, South Korea, with approximately 280,000 residents. Black carbon (BC), PM2.5, and NO2 were monitored using portable devices equipped on an electric bicycle. Results showed that in the evening (6–8 p.m.), the concentrations were higher in both commercial and residential areas compared to the background location, while concentrations were notably elevated only in roadside areas in the morning (8–10 a.m.). Spatial mapping of measured concentrations revealed that the highest concentrations corresponded to areas with densely operated charbroiling meat-cooking restaurants. Additionally, it was confirmed that BC and PM2.5 emitted from the commercial areas influenced nearby recreational areas (e.g., streamside roads). In conclusion, this study demonstrated that air pollutant hotspots resulting from human activities, such as dining at commercial restaurants, significantly worsen the local air quality on a small scale. Efforts to reduce the uncontrolled emissions of air pollutants from charbroiling meat-cooking restaurants are necessary.

Atmospheric Teleconnections Responsible for the Dominant Patterns of Interannual Variability in Summer Drought over Northern Asia

Abstract Summer drought over northern Asia (NA) seriously threatens the local fragile ecological environment and social economy development. In this study, using the standardized precipitation evapotranspiration index (SPEI), we first identify the dominant modes of interannual variability in summer drought condition over NA and then explore the atmospheric patterns responsible for the formation of the modes. The results show that the first empirical orthogonal function (EOF1) mode of summer SPEI over NA exhibits a meridional dipole pattern, which is influenced primarily by the polar–Eurasian teleconnection (POL) and circumglobal teleconnection (CGT) patterns. Under the influence of negative POL and positive CGT patterns, there is an anomalous anticyclone (cyclone) over northwestern Siberia (Lake Baikal to Northeast China). Such atmospheric circulations lead to meridional dipole patterns in air temperature, moisture condition, vertical motion, and cloud cover over NA, favoring decreased (increased) precipitation and increased (decreased) potential evapotranspiration over northern (southern) NA, finally contributing to the formation of EOF1. The second EOF (EOF2) shows an approximate zonal dipole pattern, which is influenced by the British–Baikal Corridor (BBC) and Scandinavia (SCA) teleconnection patterns. The positive BBC and SCA patterns can lead to an anomalous anticyclone over the Ural Mountains and a cyclone over Lake Baikal. Such atmospheric circulations result in a zonal dipole pattern in precipitation and potential evapotranspiration over NA through changing the local moisture condition, air temperature, and radiation, consequently favoring the formation of EOF2. Fitting analysis indicates that the aforementioned atmospheric factors can explain 76% (55%) of the interannual variability of EOF1 (EOF2).

Assessing the impact of climate change on aircraft engine performance during different flight phases (take-off and cruise) and the environmental consequences

PurposeClimate change significantly impacts global temperatures, posing challenges to various sectors, including aviation. The purpose of this study is to assess the impact of climate change on aircraft engine performance during different flight phases (take-off and cruise) and the environmental consequences.Design/methodology/approachThis study examines the effects of rising temperatures on aircraft engine performance using real-time data from a Boeing 787-8 equipped with GEnx-1B engines, which are collected via Flight Data Recorder of the engines and were analyzed for the take-off and cruise phases on the ground. Exhaust gas temperature (EGT), fuel flow and take-off weights were evaluated.FindingsThe analysis revealed a significant increase in EGT at the cruising altitude of 38,000 ft during the summer months compared to expected standard atmospheric values. This increase, averaging over 200 °C, is attributed to global warming. Such elevated temperatures are likely to accelerate the degradation of turbine components, resulting in increased fuel consumption: higher EGT signifies inefficient engine operation, resulting in more fuel burned per unit thrust; early engine aging: elevated temperatures accelerate wear and tear on turbine components, potentially reducing engine lifespan and increasing maintenance costs and enhanced atmospheric pollution: incomplete combustion at high EGTs generates additional emissions, contributing to local air quality concerns.Practical implicationsThe research findings have practical implications for understanding the potential operational challenges and environmental impacts of climate change on aircraft engine performance. This lets us explore mitigation strategies and adapt operational procedures to ensure sustainable regional aviation practices.Originality/valueThis research enhances environmental consequences by assessing the impact of climate change on aircraft performance.

Modern technologies for medical rehabilitation of children with knee joint injuries

Pathology of the knee joint in children is a pressing problem in pediatric traumatology, orthopedics and pediatrics. The frequency of injuries to the knee joint is determined by the complexity of its structure, biomechanical features with a high probability of overload. At the same time, intra-articular injuries in children and adolescents, accounting for up to 7 % in the structure of inpatient pathology, are the cause of pronounced functional disorders of the lower limb and the risk of developing post-traumatic osteoarthritis Currently, physical factors are widely used at various stages of medical rehabilitation of children with damage to the capsular-ligamentous apparatus of the knee joint. The conducted studies have established the effectiveness of using local air cryotherapy in the early postoperative period, characterized by a pronounced anti-edematous, analgesic effect. Early regression of pain and elimination of microcirculatory disorders in the area of injury as a result of a course of pulsed low-frequency magnetic therapy at various stages of medical rehabilitation of children with damage to the capsular-ligamentous apparatus of the knee joint have been recorded. The beneficial effect of a pulsed low-frequency electrostatic field on indicators of orthopedic status, and thermography indicators in the area of injury in children with knee joint injuries has been established. Data were obtained on more pronounced regression of pain, earlier restoration of range of motion in the damaged joint and relief of signs of post-traumatic synovitis with the complex use of a pulsed low-frequency electrostatic field and robotic mechanotherapy in children with damage to the capsular ligamentous apparatus of the knee joint. The obtained clinical and functional results are of great importance for injuries of the knee joint with the risk of contractures in the postoperative period.

Dynamic energy optimization strategy to provide appropriate thermal comfort and fresh air under occupants’ different activity types

An effective strategy for optimizing indoor air distribution in stratum ventilation heating systems under different types of human activity has been proposed, in order to provide appropriate thermal comfort while exploiting the potential for energy savings. The stratum ventilation was optimized using strategy 1 (the optimization strategy of three ventilation performance indicators based on VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR)), the strategy 2 (the optimization strategy with constraint based on VIKOR) and the strategy 3 (the optimization strategy aimed at energy conservation), respectively. These strategies provide optimal indoor air distribution within a stratum ventilation system that is influenced by various factors (i.e. supply air temperature, supply air vane angle, supply air velocity, metabolic rate, clothing insulation and outdoor air temperature). Firstly, the parameters of the stratum ventilation system are obtained using Computational Fluid Dynamics (CFD) software. In addition, using the simulation results as input variables, predictive models of ventilation performance (i.e., PMV, local mean air age (LMAA) and energy consumption) was developed using Artificial Neural Network (ANN). Finally, by optimizing the proposed ANN based strategy 1, strategy 2 and strategy 3, the ventilation performance is output. The proposed strategy 1 provides a comfortable indoor environment and saves energy, and compared to the strategy 1, the strategy 3 saves more energy while ensuring that thermal comfort meets the requirements. In addition, considering the optimization of clothing insulation while providing appropriate thermal comfort also indirectly saves energy. Moreover, these strategies also work well as the outdoor air temperature changes.

Attributable deaths in Austria due to ozone under different climate scenarios.

Tropospheric ozone is an air pollutant that poses a public health problem in Europe. Climate change could increase the formation of ozone. Applying past and predicted annual total (all-cause) mortality data and modeled daily ozone concentrations, we performed a nationwide health impact assessment estimating annual ozone-related (attributable) deaths in Austria. Different approaches were compared. Estimates were based on maximal 1-h averages of ozone. Until the decade from 2045 till 2055, more people will die in Austria because of the demographic trends. Therefore, more deaths will also be attributable to ozone. Higher greenhouse gas emission scenarios (e.g. Representative Concentration Pathway RCP8.5 compared to RCP2.6) will lead to more ozone-related deaths, mostly due to the national emission of ozone precursors (a difference of 250-340 cases per year, depending on the model), but to a lesser extent because of global climate change. Increases in attributable deaths will be affected mostly by national, not global mitigation measures. National emission reduction will certainly have a strong and beneficial effect on local atmospheric chemistry, air quality, and public health.