Wildfire smoke (WFS) is an urgent and rapidly growing threat to global health. Aside from obvious threats to pulmonary function, increases in cardiac abnormalities or myocardial infarction have been documented during WF season, but little is known about the effects of WFS on cardiovascular health. We investigated the effect of nonoccupational WFS exposure on cardiovascular and pulmonary function at rest and during graded handgrip exercise through a case series of young, healthy adults (n = 4, 25 ± 6 years) assessed after ≥3 days of bad or good air quality. Peripheral and estimated central blood pressures, vascular stiffness, and microvascular function (Near infrared spectroscopy, NIRS) were assessed at rest, and during rhythmic handgrip exercise. WFS did not appear to alter resting peripheral, central BP, or vascular stiffness (all, p > 0.05). Slope 1 and slope 2 from the NIRS-vascular occlusion test (NIRS-VOT) were not different between conditions (p > 0.05). The change in SmO2 during exercise was lower (p = 0.02, η p 2 $$ {\\eta}_{\\mathrm{p}}^2 $$  = 0.62) with bad air quality. These preliminary findings suggest modest effects of environmental WFS exposure on muscle microvascular function during exercise in healthy adults. Future work is needed to elucidate the physiological changes with WFS exposure and the increased risk of cardiovascular events, perhaps exacerbated through physical activity.

Air pollution is a matter of great significance that confronts the sustainable progress of urban areas. Against India\'s swift urbanization, several urban areas exhibit the coexistence of escalating populace and expansion in developed regions alongside extensive spatial heterogeneity. The interaction mechanism between the growth of urban areas and the expansion of cities holds immense importance for the remediation of air pollution. Henceforth, the present investigation utilizes geographically weighted regression (GWR) to examine the influence of urban expansion and population growth on air quality. The examination will use a decade of data on the variation in PM2.5 levels from 2010 to 2020 in eight Indian metropolitan cities. The study\'s findings demonstrate a spatial heterogeneity between urban growth dynamics and air pollution levels. Urban growth and the expansion of cities demonstrate notable positive impacts on air quality, although the growth of infilling within expanding urban areas can significantly affect air quality. Given the unique trajectories of urban development in developing countries, this research provides many suggestions for urban administrators to foster sustainable urban growth.

The ventilation of buildings is crucial to ensure indoor health, especially when demanding physical activities are carried out indoors, and the pandemic has highlighted the need to develop new management methods to ensure adequate ventilation. In Spain, there are no specific ventilation regulations to prevent the spread of pathogens such as the coronavirus. Therefore, it is necessary to have a theoretical tool for calculating occupancy to maintain sports facilities in optimal safety conditions. The proposed theoretical method is based on the analysis of mathematical expressions from European standardisation documents and uses the concentration of CO2 as a bioeffluent. It is also based on the concept of background and critical concentration, which allows its application to be extrapolated to future crises caused by pathogens. This study presents a unique and novel dataset for sports centres. For this purpose, the calculation methods were applied to the data set provided by Mostoles City Council, Spain, during the pandemic years with the highest incidence of COVID-19, when the government introduced the assimilation of COVID-19 sick leave to occupational accidents. The data on this type of sick leave provided by the City Council correspond to the period between March 2020 and February 2022. Similarly, the data on the average use of sports facilities by activity, provided by the Sports Department, correspond to the years 2020 and 2021. In this way, it was possible to verify the effectiveness in preventing the spread of any type of coronavirus. In conclusion, the implementation of a theoretical occupancy calculation method based on the concentration of carbon dioxide as a bioeffluent can be an effective tool for the management of future crises caused by pathogens or hazardous chemicals in the air, and demonstrated its effectiveness in sports centres such as gyms, sports fields, and indoor swimming pools during the COVID-19 pandemic.

Wildfires are a significant threat to human health, in part through degraded air quality. Prescribed burning can reduce wildfire severity but can also lead to an increase in air pollution. The complexities of fires and atmospheric processes lead to uncertainties when predicting the air quality impacts of fire and make it difficult to fully assess the costs and benefits of an expansion of prescribed fire. By modeling differences in emissions, surface conditions, and meteorology between wildfire and prescribed burns, we present a novel comparison of the air quality impacts of these fire types under specific scenarios. One wildfire and two prescribed burn scenarios were considered, with one prescribed burn scenario optimized for potential smoke exposure. We found that PM2.5 emissions were reduced by 52%, from 0.27 to 0.14 Tg, when fires burned under prescribed burn conditions, considerably reducing PM2.5 concentrations. Excess short-term mortality from PM2.5 exposure was 40 deaths for fires under wildfire conditions and 39 and 15 deaths for fires under the default and optimized prescribed burn scenarios, respectively. Our findings suggest prescribed burns, particularly when planned during conditions that minimize smoke exposure, could be a net benefit for the impacts of wildfires on air quality and health.

The occurrence of waste fires in unscientifically managed landfill sites has become a pressing environmental issue in the urban centers of developing economies. In the present work, an investigation was carried out to evaluate the air quality implications of three major fire events that occurred at the Brahmapuram Municipal Solid Waste Treatment Plant (BMSWTP) in Kochi, India. Initially, Landsat-based surface temperature monitoring was conducted to identify the thermal hotspots within the landfill. The emissions of different pollutants during waste fires were quantified and compared between satellite-based ex-situ and field-based in-situ methods. The dispersion patterns of PM2.5 particles released during the fires were visualised using the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) particle dispersion model. The Landfill Gas Emissions Model (LandGEM) was employed to quantify the greenhouse gases (GHGs) released during waste storage, which was then compared with the GHGs emissions during waste fires. In-situ emission estimates showed that the combustion of waste at BMSWTP led to the release of 909.3 MT of PM10, 938.8 MT of PM2.5, 5832.9 MT of CO, 43.6 MT of SOx, 284.2 MT of NOx, 138,941.9 MT of CO2, 426.8 MT of CH4, and 2665.1 MT of VOC. However, a noticeable disparity was observed between the in-situ and ex-situ emission estimates, wherein the latter underestimated the actual emissions. Most of the emitted PM2.5 particles propagated oceanward under the influence of prevailing winds, covering the densely populated areas of Kochi municipal corporation. The amount of CH4 and CO2 emitted during the waste fires was on par with the emissions from 159 days of waste storage for CH4 and 51.8 years of waste storage for CO2, with a cumulative global warming potential of 147.9 Gg CO2-e.

Since the start of the twenty-first century, China\'s economy has grown at a high or moderate rate, and air pollution has become increasingly severe. The study was conducted using data from remote sensing observations between 1998 and 2019, employing the standard deviation ellipse model and spatial autocorrelation analysis, to explore the spatiotemporal distribution characteristics of PM2.5 in Henan Province. Additionally, a multiscale geographically weighted regression model (MGWR) was applied to explore the impact of 12 driving factors (e.g., mean surface temperature and CO2 emissions) on PM2.5 concentration. The research revealed that (1) Over a period of 22 years, the yearly mean PM2.5 concentrations in Henan Province demonstrated a trend resembling the shape of the letter \"M\", and the general trend observed in Henan Province demonstrated that the spatial center of gravity of PM2.5 concentrations shifted toward the north. (2) Distinct spatial clustering patterns of PM2.5 were observed in Henan Province, with the northern region showing a primary concentration of spatial hot spots, while the western and southern areas were predominantly characterized as cold spots. (3) MGWR is more effective than GWR in unveiling the spatial heterogeneity of influencing factors at various scales, thereby making it a more appropriate approach for investigating the driving mechanisms behind PM2.5 concentration. (4) The results acquired from the MGWR model indicate that there are varying degrees of spatial heterogeneity in the effects of various factors on PM2.5 concentration. To summarize the above conclusions, the management of the atmospheric environment in Henan Province still has a long way to go, and the formulation of relevant policies should be adapted to local conditions, taking into account the spatial scale effect of the impact of different influencing factors on PM2.5.

Urban greenhouse gas emissions monitoring is essential to assessing the impact of climate mitigation actions. Using atmospheric continuous measurements of air quality and carbon dioxide (CO2), we developed a gradient-descent optimization system to estimate emissions of the city of Paris. We evaluated our joint CO2-CO-NOx optimization over the first SARS-CoV-2 related lockdown period, resulting in a decrease in emissions by 40% for NOx and 30% for CO2, in agreement with preliminary estimates using bottom-up activity data yet lower than the decrease estimates from Bayesian atmospheric inversions (50%). Before evaluating the model, we first provide an in-depth analysis of three emission data sets. A general agreement in the totals is observed over the region surrounding Paris (known as Île-de-France) since all the data sets are constrained by the reported national and regional totals. However, the data sets show disagreements in their sector distributions as well as in the interspecies ratios. The seasonality also shows disagreements among emission products related to nonindustrial stationary combustion (residential and tertiary combustion). The results presented in this paper show that a multispecies approach has the potential to provide sectoral information to monitor CO2 emissions over urban areas enabled by the deployment of collocated atmospheric greenhouse gases and air quality monitoring stations.

Air pollution is a major risk factor of cardiovascular disease (CVD). To date, limited studies have estimated the effects of ambient air pollution on CVD mortality using high-resolution exposure assessment, which might fail to capture the spatial variation in exposure and introduce bias in results. Besides, the three-year action plan (TYAP, 2018-2020) was released; thus, the constitution and health effect of air pollutants may have changed. In this study, we estimated the short-term effect exposed to particulate matters with parameter less than 2.5 µm (PM2.5) and ozone (O3) with 0.05° × 0.05° resolution on CVD mortality and measured the influence of TYAP in the associations. We used random forest models with spatial weight matrices to attain high-resolution pollutant concentrations and conditional Poisson regression to assess the relationship between air pollution and cardiovascular mortality. With an increase of 10 µg/m3 in PM2.5 and O3 during 2018-2021 in the Sichuan Basin (SCB), CVD mortality increased 1.0134 (95% CI 1.0102, 1.0166) and 1.0083 (95% CI 1.0060, 1.0107), respectively, using high-resolution air pollutant concentration, comparing to 1.0070 (95% CI 1.0052, 1.0087) and 1.0057 (95% CI 1.0037, 1.0078) using data from air quality monitoring stations (AQMs). After TYAP, the relative risk (RR) due to PM2.5 rose up to 1.0149 (95% CI 1.0054, 1.0243), and the RR due to O3 rose up to 1.0089 (95% CI 1.0030, 1.0148) in Sichuan Province. We found significantly positive association of cardiovascular mortality and air pollution in Sichuan Province. And using high-resolution exposure would be more accurate to estimate the effect of air pollution on CVD. After TYAP, the cardiovascular mortality risk estimation due to PM2.5 decreased in elderly in SCB, and the risk due to O3 increased in Sichuan Province.

Setting nitrogen (N) emission targets for agricultural systems is crucial to prevent to air and groundwater pollution, yet such targets are rarely defined at the county level. In this study, we employed a forecasting-and-back casting approach to establish human health-based nitrogen targets for air and groundwater quality in Quzhou county, located in the North China Plain. By adopting the World Health Organization (WHO) phase I standard for PM2.5 concentration (35 μg m-3) and a standard of 11.3 mg NO3--N L-1 for nitrate in drinking water, we found that ammonia (NH3) emissions from the entire county must be reduced by at least 3.2 kilotons year-1 in 2050 to meet the WHO\'s PM2.5 phase I standard. Additionally, controlling other pollutants such as sulfur dioxide (SO2) and nitrogen oxides (NOx) is necessary, with required reductions ranging from 16% to 64% during 2017-2050. Furthermore, to meet the groundwater quality standard, nitrate nitrogen (NO3--N) leaching to groundwater should not exceed 0.8 kilotons year-1 by 2050. Achieving this target would require a 50% reduction in NH3 emissions and a 21% reduction in NO3--N leaching from agriculture in Quzhou in 2050 compared to their respective levels in 2017 (5.0 and 2.1 kilotons, respectively). Our developed method and the resulting N emission targets can support the development of environmentally-friendly agriculture by facilitating the design of control strategies to minimize agricultural N losses.

In the 1990s, a sampling network for the biomonitoring of forests using epiphytic lichen diversity was established in the eastern Iberian Peninsula. This area registered air pollution impacts by winds from the Andorra thermal power plant, as well as from photo-oxidants and nitrogen depositions from local and long-distance transport. In 1997, an assessment of the state of lichen communities was carried out by calculating the Index of Atmospheric Purity. In addition, visible symptoms of morphological injury were recorded in nine macrolichens pre-selected by the speed of symptom evolution and their wide distribution in the territory. The thermal power plant has been closed and inactive since 2020. During 2022, almost 25 years later, seven stations of this previously established biomonitoring were revaluated. To compare the results obtained in 1997 and 2022, the same methodology was used, and data from air quality stations were included. We tested if, by integrating innovative methodologies (NIRS) into biomonitoring tools, it is possible to render an integrated response. The results displayed a general decrease in biodiversity in several of the sampling plots and a generalised increase in damage symptoms in the target lichen species studied in 1997, which seem to be the consequence of a multifactorial response.