Impact on mortality of biomass combustion from wildfires in Spain: A regional analysis

How air pollution affects cause-specific emergency hospital admissions on days with biomass combustion in Spain?

Although wildfires are growing in number, intensity and extent due to climate change, few studies have been undertaken to analyse their health impact, and fewer still to analyse the impact of variables other than particulate matter. The objective of this study is to analyse the short-term impact of NO2, PM10, PM2.5, O3 and temperature in heat waves on emergency hospital admissions in Spain on days when biomass combustion occurs. We conducted an ecological longitudinal time series study across the period 2013-2018. The dependent variables were emergency hospital admissions due to all causes (ICD-10: A00-R99), circulatory causes (ICD-10: I00-I99) and respiratory causes (ICD-10: J00-J99) in 9 representative Spanish provinces. The independent variables were daily mean air pollution concentrations measured at a provincial level. We also included daily maximum temperatures recorded at reference observatories in the respective provinces. Poisson generalised linear models were fitted for days with and without PM advections due to biomass burning smoke. We controlled for trends, seasonalities, the autoregressive nature of the series, Sundays and Public Holidays. Days with biomass burning smoke advections increased PM concentrations in all provinces and ozone in many of them, something that did not occur in equal measure in the case of NO2. Nevertheless, the principal impact on admissions was due to O3, followed by NO2, PM, and lastly, heat-wave temperatures. This pattern was observed for all three causes analysed. The role of PM was relegated to that of a third factor, and the role of temperature to an order of lesser magnitude than that of chemical pollution. To focus the health impacts of wildfires exclusively on the impact of PM concentrations would be to minimise their real impact on population health. It is therefore essential to implement integrated plans that take into account the joint effect of all atmospheric variables affected.

Does the new European Union air quality directive really protect health? A nationwide case study in Spain

In October 2024, the European Union (EU) issued a Directive establishing a series of limit values, which, once transposed into national law by EU Member States, will become mandatory. This Directive is less restrictive than the WHO guideline values published in 2021. Using dose-response functions specifically calculated for every Spanish province, this study sought to ascertain how many short-term, all-cause hospital emergency admissions (ICD-9: 1-799 and ICD-10: A00-R99) were attributable to NO2, PM10 and PM2.5 concentrations across the period 2013-2018, and what the ensuing reduction in admissions would be, if the EU Directive and WHO guideline values were applied respectively. The results obtained indicate that here in Spain some 38,790 admissions per year are attributable to NO2, PM10 and PM2.5 pollution, at a total cost of €548 million. These admissions would be reduced by 478 (1.23 %) if the EU Directive were observed, and by 4496 (11.59 %) if the WHO guideline values were met. While compliance with the EU limit values would have almost no effect in terms of a decrease in attributable admissions, such an effect would indeed be seen in the event of compliance with the WHO guideline values and would entail a saving of over €63 million nationwide. This study only focused on short-term effects of PM and NO2.

Short-term effects of fine particulate matter from biomass combustion and Saharan dust intrusions on emergency hospital admissions due to mental and behavioural disorders, anxiety and depression in Spain

Climate change is affecting both the frequency and scale of wildfires, as well as the increase in the number of days with Saharan dust intrusions. Traditionally, studies have focused on the extent to which the increase in fine particulate matter (PM) has had an impact on cardio-respiratory diseases, but (apart from PM) not on how the meteorological and pollution conditions in these situations affect other diseases, such as those linked to mental health. This study therefore sought to ascertain how daily mean PM10, PM 2.5, NO2, O3 concentrations and daily maximum temperature in heat waves influence daily emergency hospital admissions in Spain caused by mental and behavioural disorders, depression and anxiety on days with PM from biomass combustion and/or Saharan dust intrusions, as compared to days without such conditions, across the period 2009-2018. Our results indicate that on days on which there is biomass combustion, PM concentrations have a statistically significant effect on emergency admissions due to mental disorders, probably related with the toxicity of these particles. Yet on days with intrusions of Saharan dust rather than PM, it is the other variables considered in the analysis that are most closely linked to these types of admissions. The results of this study thus point to the need to implement public health prevention plans which take into account the joint effect of various environmental risk factors that act synergistically in given situations.

Fire-Pollutant-Atmosphere Components and Its Impact on Mortality in Portugal During Wildfire Seasons

This study analyzed fire-pollutant-meteorological variables and their impact on cardio-respiratory mortality in Portugal during wildfire season. Data of burned area, particulate matter with a diameter of 10 or 2.5 μm (μm) or less (PM10, PM2.5), carbon monoxide (CO), nitrogen dioxide (NO2), ozone (O3), temperature, relative humidity, wind speed, aerosol optical depth and mortality rates of Circulatory System Disease (CSD), Respiratory System Disease (RSD), Pneumonia (PNEU), Chronic Obstructive Pulmonary Disease, and Asthma (ASMA), were used. Only the months of 2011-2020 wildfire season (June-July-August-September-October) with a burned area greater than 1,000 ha were considered. Principal component analysis was used on fire-pollutant-meteorological variables to create two indices called Pollutant-Burning Interaction (PBI) and Atmospheric-Pollutant Interaction (API). PBI was strongly correlated with the air pollutants and burned area while API was strongly correlated with temperature and relative humidity, and O3. Cluster analysis applied to PBI-API divided the data into two Clusters. Cluster 1 included colder and wetter months and higher NO2 concentration. Cluster 2 included warmer and dried months, and higher PM10, PM2.5, CO, and O3 concentrations. The clusters were subjected to Principal Component Linear Regression to better understand the relationship between mortality and PBI-API indices. Cluster 1 showed statistically significant (p-value < 0.05) correlation (r) between RSDxPBI (r RSD = 0.58) and PNEUxPBI (r PNEU = 0.67). Cluster 2 showed statistically significant correlations between RSDxPBI (r RSD = 0.48), PNEUxPBI (r PNEU = 0.47), COPDxPBI (r COPD = 0.45), CSDxAPI (r CSD = 0.70), RSDxAPI (r CSD = 0.71), PNEUxAPI (r PNEU = 0.49), and COPDxAPI (r PNEU = 0.62). Cluster 2 analysis indicates that the warmest, driest, and most polluted months of the wildfire season were associated with cardio-respiratory mortality.

Effect modification of the association between fine particulate air pollution during a wildfire event and respiratory health by area-level measures of socio-economic status, race/ethnicity, and smoking prevalence

Fine particulate air pollution (PM2.5) is decreasing in most areas of the United States, except for areas most affected by wildfires, where increasing trends in PM2.5 can be attributed to wildfire smoke. The frequency and duration of large wildfires and the length of the wildfire season have all increased in recent decades, partially due to climate change, and wildfire risk is projected to increase further in many regions including the western United States. Increasingly, empirical evidence suggests differential health effects from air pollution by class and race; however, few studies have investigated such differential health impacts from air pollution during a wildfire event. We investigated differential risk of respiratory health impacts during the 2008 northern California wildfires by a comprehensive list of socio-economic status (SES), race/ethnicity, and smoking prevalence variables. Regardless of SES level across nine measures of SES, we found significant associations between PM2.5 and asthma hospitalizations and emergency department (ED) visits during these wildfires. Differential respiratory health risk was found by SES for ED visits for chronic obstructive pulmonary disease where the highest risks were in ZIP codes with the lowest SES levels. Findings for differential effects by race/ethnicity were less consistent across health outcomes. We found that ZIP codes with higher prevalence of smokers had greater risk of ED visits for asthma and pneumonia. Our study suggests that public health efforts to decrease exposures to high levels of air pollution during wildfires should focus on lower SES communities.

Forest Fire Identification in UAV Imagery Using X-MobileNet

Forest fires are caused naturally by lightning, high atmospheric temperatures, and dryness. Forest fires have ramifications for both climatic conditions and anthropogenic ecosystems. According to various research studies, there has been a noticeable increase in the frequency of forest fires in India. Between 1 January and 31 March 2022, the country had 136,604 fire points. They activated an alerting system that indicates the location of a forest fire detected using MODIS sensor data from NASA Aqua and Terra satellite images. However, the satellite passes the country only twice and sends the information to the state forest departments. The early detection of forest fires is crucial, as once they reach a certain level, it is hard to control them. Compared with the satellite monitoring and detection of fire incidents, video-based fire detection on the ground identifies the fire at a faster rate. Hence, an unmanned aerial vehicle equipped with a GPS and a high-resolution camera can acquire quality images referencing the fire location. Further, deep learning frameworks can be applied to efficiently classify forest fires. In this paper, a cheaper UAV with extended MobileNet deep learning capability is proposed to classify forest fires (97.26%) and share the detection of forest fires and the GPS location with the state forest departments for timely action.

Does the meteorological origin of heat waves influence their impact on health? A 6-year morbidity and mortality study in Madrid (Spain)

BACKGROUND

In Spain, two synoptic-scale conditions influence heat wave formation. The first involves advection of warm and dry air masses carrying dust of Saharan origin (North African Dust (NAF) = 1). The second entails anticyclonic stagnation with high insolation and stability (NAF) = 0). Some studies show that the meteorological origin of these heat waves may affect their impact on morbidity and mortality.

OBJECTIVE

To determine whether the impact of heat waves on health outcomes in Madrid (Spain) during 2013-2018 varied by synoptic-scale condition.

METHODOLOGY

Outcome data consist of daily mortality and daily hospital emergency admissions (morbidity) for natural, circulatory, and respiratory causes. Predictors include daily maximum and minimum temperatures and daily mean concentrations of NO₂, PM₁₀, PM_2.5, NO₂, and O₃. Analyses adjust for insolation, relative humidity, and wind speed. Generalized linear models were performed with Poisson link between the variables controlling for trend, seasonality, and auto-regression in the series. Relative Risks (RR) and Attributable Risks (AR) were determined. The RRs for mortality attributable to high temperatures were similar regardless of NAF status. For hospital admissions, however, the RRs for hot days with NAF = 0 are higher than for days with NAF = 1. We also found that atmospheric pollutants worsen morbidity and mortality, especially PM₁₀ concentrations when NAF = 1 and O₃ concentrations when NAF = 0.

RESULTS

The effect of heat waves on morbidity and mortality depends on the synoptic situation. The impact is greater under anticyclonic stagnation conditions than under Saharan dust advection. Further, the health impact of pollutants such as PM₁₀ and O₃ varies according to the synoptic situation.

CONCLUSIONS

Based on these findings, we strongly recommend prevention plans to include data on the meteorological situation originating the heat wave, on a synoptic-scale, as well as comprehensive preventive measures against the compounding effect of high temperatures and pollution.

Assessment of Smoke Pollution Caused by Wildfires in the Baikal Region (Russia)

Climate change has increased the prevalence of wildfires, resulting in longer fire seasons and larger geographic area burned. The aim of this work was to assess the air pollution and health risk to the population caused during exposure to smoke in fire season. The study design included: an analysis of long-term air pollution to determine background levels; an analysis of short-term (<24 h) and subchronic (10–14 days) concentrations during wildfires; and an assessment of the health risk in the industrial center of the Baikal region (Russia). In Irkutsk, at a distance of 2000 km from the fire focal points, the maximum short-term concentrations of pollution were noted during the smoke period, when the average CO level increased 2.4 times, and PM1 increased 1.4 times relative to the background levels in August 2021. In Bratsk, located near the fires, the increases in short-term concentrations were: CO—21.0; SO2—13.0; formaldehyde—12.0; TPM—4.4 times. The hazard indices of respiratory and coronary diseases in the burning period exceeded the acceptable level. Acute reactions to smoke can be expected in 30% of the exposed population near fires and 11% in remote areas (Bratsk). The results obtained from the remote sensing of atmospheric smoke can be used to urgently resolve the issue of organizing medical assistance or evacuating the population groups most sensitive to the effects of smoke in fire season.

Integrating multiple factors to optimize watchtower deployment for wildfire detection

Traditional human-vision-based watchtower systems are being gradually replaced by the machine-vision-based watchtower system. The visual range of machine-vision-based watchtower is smaller than the range of traditional human-vision-based watchtower, which has led to a sharp increase in the number of towers that should be deployed. Consequently, the overlapping area between watchtowers is larger and overlaps are more frequent than in conventional watchtower networks. This poses an urgent challenge: identifying the optimal locations for deployment. If the number of required watchtowers must be increased to extend the detection coverage, overlaps among watchtowers are inevitable and result in viewshed redundancy. However, this redundancy of the viewshed resources of the watchtowers has not been utilized in the design of fire detection systems. Moreover, fire ignition factors, such as climatic factors, fuels, and human behaviour, cause the fire occurrence risk to differ among forest areas. Thus, the fire risk map of the area should also be considered in watchtower deployment. A fire risk model is used as the first step in producing the fire risk map, which is used to propose a new watchtower deployment model for optimizing the watchtower system by integrating viewshed analysis, location allocation, and multi-coverage of the high-fire-risk area while considering the budget constraints for providing optimal coverage. We use a real dataset of a forest park to evaluate the applicability of our approach. The proposed approach is evaluated against the FV-NB (Full coVerage with No Budget constraint) algorithm and the XV-B (maXimum possible coVerage with a Budget constraint) algorithm in terms of performance. The evaluation results demonstrate that our approach realizes higher coverage gain and excellent multiple-coverage of the fire risk area by integrating the viewshed and the fire risk level into location allocation while satisfying requirements on the overall coverage and budget. The proposed approach is more suitable in the environments with moderate watchtower density, in which overlapping areas are frequent. It offers as much as 8.9-17.3% improvement of multiple-coverage of the high-fire-risk area.

A new integrative perspective on early warning systems for health in the context of climate change

Climate change causes or aggravates a wide range of exposures with multiple impacts on health, both direct and indirect. Early warning systems have been established to act on the risks posed by these exposures, permitting the timely activation of action plans to minimize health effects. These plans are usually activated individually. Although they show good results from the point of view of minimizing health impacts, such as in the case of high temperature plans, they commonly fail to address the synergies across various climate-related or climate-aggravated exposures. Since several of those exposures tend to occur concurrently, failure to integrate them in prevention efforts could affect their effectiveness and reach. Thus, there is a need to carry out an integrative approach for the multiple effects that climate change has on population health. This article presents a proposal for how these plans should be articulated. The proposed integrated plan would consist of four phases. The first phase, based on early warning systems, would be the activation of different existing individual plans related to the health effects that can be caused by certain circumstances and when possible corrective measures would be implemented. The second phase would attempt to quantify the health impact foreseen by the event in terms of the different health indicators selected. The third phase would be to activate measures to minimize the impact on health, via population alerts and advisories, and additional social and health services, based on the provisions in phase two. Phase four would be related to epidemiological surveillance that permits evaluation of the effects of activating the plan. We believe that this integrative approach should be extended to all of the public health interventions related to climate change.

Characterization of organic aerosol at a rural site influenced by olive waste biomass burning

Biomass burning is a major air pollution problem all around the world. However, the identification and quantification of its contribution to ambient aerosol levels is a difficult task due to the generalized lack of observations of molecular markers. This paper presents the results of a yearlong study of organic constituents of the atmospheric aerosol at a rural site in southern Spain (Villanueva del Arzobispo, Jaén). Sampling was performed for PM₁₀ and PM_2.5, and a total of 116 and 115 samples, respectively, were collected and analyzed by GC/MS, quantifying 77 organic compounds. Higher levels of organic pollutants were recorded from November to March, coinciding with the cold season when domestic combustion is a common practice in rural areas. This jointly with adverse meteorological conditions, e.g. strong atmospheric stability, produced severe pollution episodes with high PM_x ambient levels. High daily concentrations of tracers were reached, up to 26 ng m^-3 for B(a)P and 6065 ng m^-3 for levoglucosan in PM_2.5, supporting that biomass burning is a major source of pollution at rural areas. A multivariate statistical study based on factor and cluster analysis, was applied to the data set with the aim to distinguish sources of organic compounds. The main resulting sources were related with biomass combustion, secondary organic aerosol (SOA), biogenic emissions, lubricating oil and soil organic components. A preliminary organic source profile for olive wastes burning was evaluated, based on cluster results, showing anhydrosacharides and xylitol are the main emitted compounds, accounting for more than 85% of the quantified compounds. Other source compounds were fatty acids, diacids, aliphatics, sugars, sugar alcohols, PAHs and quinones.

Wildfire and prescribed burning impacts on air quality in the United States

Air quality impacts from wildfires have been dramatic in recent years, with millions of people exposed to elevated and sometimes hazardous fine particulate matter (PM _2.5 ) concentrations for extended periods. Fires emit particulate matter (PM) and gaseous compounds that can negatively impact human health and reduce visibility. While the overall trend in U.S. air quality has been improving for decades, largely due to implementation of the Clean Air Act, seasonal wildfires threaten to undo this in some regions of the United States. Our understanding of the health effects of smoke is growing with regard to respiratory and cardiovascular consequences and mortality. The costs of these health outcomes can exceed the billions already spent on wildfire suppression. In this critical review, we examine each of the processes that influence wildland fires and the effects of fires, including the natural role of wildland fire, forest management, ignitions, emissions, transport, chemistry, and human health impacts. We highlight key data gaps and examine the complexity and scope and scale of fire occurrence, estimated emissions, and resulting effects on regional air quality across the United States. The goal is to clarify which areas are well understood and which need more study. We conclude with a set of recommendations for future research.

IMPLICATIONS

In the recent decade the area of wildfires in the United States has increased dramatically and the resulting smoke has exposed millions of people to unhealthy air quality. In this critical review we examine the key factors and impacts from fires including natural role of wildland fire, forest management, ignitions, emissions, transport, chemistry and human health.

Short-term effects of drought on daily mortality in Spain from 2000 to 2009

Spain is a country of southern Europe that is prone to drought, and it is likely that this type of hydrological extreme will become substantially more frequent and intense in the 21st century, which could lead to greater health risks if adequate adaptive measures are not taken. For the first time, we calculated the relative risks (RRs) of daily natural (ICD10: A00-R99), circulatory (ICD10: I00-I99), and respiratory (ICD: J00-J99) mortality associated with drought events in each province of Spain from 2000 to 2009. For this purpose, we compared the performance of the Standardized Precipitation Index (SPI) and Standardized Precipitation- Evapotranspiration Index (SPEI) obtained at 1 month of accumulation (denoted as SPI-1/SPEI-1) to estimate the short-term risks of droughts on daily mortality using generalised linear models. Attributable risks were calculated from the RR data. The main findings of this study revealed statistically significant associations between the different causes of daily mortality and drought events for the different provinces of Spain, and clear spatial heterogeneity was observed across the country. Western Spain (northwest to southwest) was the region most affected, in contrast to northern and eastern Spain, and daily respiratory mortality was the group most strongly linked to the incidence of drought conditions. Moreover, for a considerable number of provinces, the effect of SPI-1 and SPEI-1 largely reflected the impact of atmospheric pollution and/or heatwaves; however, for other regions, the effect of drought conditions on daily mortality remained when these different climatic events were controlled in Poisson models. When the performances of the SPEI and SPI were compared to identify and estimate the risks of drought on daily mortality, the results were very similar, although there were slight differences in the specific causes of daily mortality.

Short-term effects of Saharan dust intrusions and biomass combustion on birth outcomes in Spain

The objective of this study is to analyze the short-term effects of atmospheric pollutant concentrations (PM₁₀, NO₂ and O₃) and heat and cold waves on the number of pre-term births and cases of low birth weight related to Saharan dust advection and biomass combustion. The dependent variables used in this analysis were the total number of births, births with low weight (>2.500 g) and pre-term births (<37 weeks), that occurred at the province level. Data provided by the NSI included: days with Saharan dust intrusion or biomass advection classified in terms of information provided by MITECO for each of the nine regions in Spain. A representative city was selected for reach region in which the registered average daily concentrations of PM₁₀, NO₂ and O₃ (μg/m³) were used. These were also provided by MITECO. The daily maximum and daily minimum temperature (°C) used was those registered by the meteorological observatory station located in each province capital, provided by AEMET. Using Poisson log linear regression models, the associated relative risks (RR) were measured as well as the population attributable risk (PAR) corresponding to the variables that resulted statistically significant at p < 0.05 for days with and without intrusion of natural particulate matter. The results obtained show that the days with Saharan dust intrusion or advections due to biomass combustion- beyond the impact of PM₁₀, primary pollutants such as NO₂ (in Saharan intrusions), heat waves and O₃ - are associated with the number of births, low birth weight and pre-term birth. The RR and percent PAR of the pollutants and the heat waves are greater than those obtained for PM₁₀. The results of this study indicate that days with natural particulate matter due to biomass combustion or advection of Saharan dust put pregnant women at risk.

Effects on daily mortality of droughts in Galicia (NW Spain) from 1983 to 2013

Climate change scenarios indicate an increase in the intensity and frequency of droughts in several regions of the world in the 21st century, especially in Southern Europe, highlighting the threat to global health. For the first time, a time-series diagnostic study has been conducted regarding the impact of droughts in Galicia, a region in north-western Spain, on daily natural-cause mortality, daily circulatory-cause mortality, and daily respiratory-cause mortality, from 1983 to 2013. We analysed the drought periods over the area of interest using the daily Standardized Evapotranspiration-Precipitation Index (SPEI) and the daily Standardized Precipitation Index (SPI), obtained at various timescales (1, 3, 6, 9 months), to identify and classify the intensity of drought and non-drought periods. Generalized linear models with the Poisson regression link were used to calculate the Relative Risks (RRs) of different causes of mortality, and the percentage of Attributable Risk Mortality (%AR) was calculated based on RRs data. According to our findings, there were statistically significant (p < 0.05) associations between drought periods, measured by both the daily SPEI and SPI, and daily mortality in all provinces of Galicia (except Pontevedra) for different timescales. Furthermore, drought periods had a greater influence on daily mortality in the interior provinces of Galicia than in the coastal regions, with Lugo being the most affected. In short term, the effect of droughts (along with heatwaves) on daily mortality was observed in interior regions and was mainly explained by atmospheric pollution effect throughout 2000 to 2009 period in Ourense, being respiratory causes of mortality the group most strongly associated. The fact that droughts are likely to become increasingly frequent and intense in the context of climate change and the lack of studies that have considered the impact of droughts on specific causes of mortality make this type of analysis necessary.

Terrain-influenced incremental watchtower expansion for wildfire detection

Optimizing the effectiveness of early wildfire detection systems is of significant interest to the community. To this end, watchtower-based wildfire observations are continuing to be practical, often in conjunction with state-of-the-art technologies, such as automated vision systems and sensor networks. One of the major challenges that the community faces is the optimal expansion of existing systems, particularly in multiple stages due to various practical, political and financial constraints. The notion of incremental watchtower expansion while preserving or making minimal changes to an existing system is a challenging task, particularly while meeting coverage and financial constraints. Conventionally and historically, this problem has been treated as a multi-objective optimization problem, and as such, currently employed methods are predominantly focused on the full-fledged optimization problem, where the problem is re-solved every time during the expansion process. In this paper, for the first time, we propose an alternative approach, by treating the expansion as a submodular set-function maximization problem. By theoretically proving that the expansion problem is a submodular set-function maximization problem, we provide four different models and matching algorithms to handle various cases that arise during the incremental expansion process. Our evaluation of the proposed approach on a practical dataset from a forest park in China, namely, the NanJing forest park, shows that our algorithms can provide an excellent coverage by integrating visibility analysis and location allocation while meeting the stringent budgetary requirements. The proposed approach can be adapted to areas of other countries.

An approach estimating the short-term effect of NO2 on daily mortality in Spanish cities

BACKGROUND

Road traffic is the most significant source of urban air pollution. PM_2.5 is the air pollutant whose health effects have been most closely studied, and is the variable most commonly used as a proxy indicator of exposure to air pollution, whereas evidence on NO₂ concentrations per se is still under study. In the case of Spain, there are no specific updated studies which calculate short-term NO₂-related mortality.

OBJECTIVE

To quantify the relative risks (RRs) and attributable risks (ARs) of daily mortality associated with NO₂ concentrations recorded in Spain across the study period, 2000-2009; and to calculate the number of NO₂-related deaths.

MATERIAL AND METHODS

We calculated daily mortality due to natural causes (ICD-10: A00 R99), circulatory causes (ICD-10: I00 I99) and respiratory causes (ICD-10: J00 J99) for each province across the period 2000-2009, using data supplied by the National Statistics Institute. Mean daily NO₂ concentrations in μg/m³ for each provincial capital were furnished by the Ministry of Agriculture & Environment, along with the equivalent figures for the control pollutants (PM₁₀). To estimate RRs and ARs, we used generalised linear models with a Poisson link, controlling for maximum and minimum daily temperature, trend of the series, seasonalities, and the autoregressive nature of the series. A meta-analysis with random effects was used to estimate RRs and ARs nationwide.

RESULTS

The overall RRs obtained for Spain, corresponding to increases of 10 μg/m³ in NO₂ concentrations were 1.012 (95% CI: 1.010 1.014) for natural-cause mortality, 1.028 (95% CI: 1.019 1.037) for respiratory-cause mortality, and 1.016 (95% CI: 1.012 1.021) for circulatory-cause mortality. This amounted to an annual overall 6085 deaths (95% CI: 3288 9427) due to natural causes, 1031 (95% CI: 466 1585) due to respiratory causes, and 1978 (95% CI: 828 3197) due to circulatory causes.

CONCLUSION

By virtue of the number of cities involved and the nature of the analysis performed, with quantification of the RRs and ARs of the short-term impact of NO₂ on daily mortality in Spain, this study provides an updated estimate of the effect had by this type of pollutant on causes of mortality, and constitutes an important basis for reinforcing public health measures at a national level.