The ambient air quality in a city is heavily influenced by meteorological conditions. The city of Siliguri, known as the "Gateway of Northeast India", is a major hotspot of air pollution in the Indian state of West Bengal. Yet almost no research has been done on the possible impacts of meteorological factors on criterion air pollutants in this rapidly growing urban area. From March 2018 to September 2022, the present study aimed to determine the correlations between meteorological factors, including daily mean temperature (℃), relative humidity (%), rainfall (mm), wind speed (m/s) with the concentration of criterion air pollutants (PM2.5, PM10, NO2, SO2, CO, O3, and NH3). For this research, the trend of all air pollutants over time was also investigated. The Spearman correlation approach was used to correlate the concentration of air pollutants with the effect of meteorological variables on these pollutants. Comparing the multiple linear regression (MLR) and non-linear regression (MLNR) models permitted to examine the potential influence of meteorological factors on concentrations of air pollutants. According to the trend analysis, the concentration of NH3 in the air of Siliguri is rising, while the concentration of other pollutants is declining. Most pollutants showed a negative correlation with meteorological variables; however, the seasons impacted on how they responded. The comparative regression research results showed that although the linear and non-linear models performed well in predicting particulate matter concentrations, they performed poorly in predicting gaseous contaminants. When considering seasonal fluctuations and meteorological parameters, the results of this research will definitely help to increase the accuracy of air pollution forecasting near future. 

https://link.springer.com/content/pdf/10.1007/s40808-022-01670-6.pdf

Investigating the association between air pollutants’ concentration and meteorological parameters in a rapidly growing urban center of West Bengal, India: a statistical modeling-based approach

The frequency and severity of wildfires have been sharply increasing due to climate change, which largely contributes to ambient particulate matter (PM) pollution. We conducted a systematic review focusing on the short-term relationships between PM attributable to wildfires (wildfire-specific PM) and diverse respiratory endpoints, with a comparison between the effects of wildfire-specific PM vs. all-source/non-wildfire PM. A comprehensive online search for the literature published from 2000 to 2022 was conducted through PubMed, Web of Sciences, Scopus, and EMBASE. We applied search terms related to wildfire smoke and respiratory health outcomes. In total, 3196 articles were retrieved, and 35 articles were included in this review. Most studies focused on the associations of wildfire-specific PM with an aerodynamic diameter of <2.5 μm (PM2.5) with respiratory emergency department visits or hospitalizations, with a time-series or case-crossover study design. Studies were mostly conducted in the United States, Canada, and Australia. Positive associations of wildfire-specific PM with respiratory morbidity were observed in most studies. Studies that focused on respiratory mortality were limited. Females can be more vulnerable to the respiratory impacts of wildfire PM, while the evidence of vulnerable subpopulations among different age groups was inconclusive. Few studies compared the effects of wildfire-specific vs. all-source/non-wildfire PM, and some reported higher levels of toxicity of wildfire-specific PM, potentially due to its distinct chemical and physical compositions. Asthma and chronic obstructive pulmonary disease were the most studied diseases, and both were adversely affected by wildfire-specific PM. To our knowledge, this is the first review that systematically summarized the associations of wildfire-specific PM exposure with adverse respiratory outcomes and compared associations of wildfire-specific vs. all-source/non-wildfire PM. Further investigations may add to the literature by examining the impacts on respiratory mortality and the effects of specific PM components from different types of wildfires. 

Associations between short-term exposure to wildfire particulate matter and respiratory outcomes: A systematic review

Ambient air quality is the most important environmental factor affecting human health, estimated by the WHO to be responsible for 4.2 million deaths annually. Having timely estimates for air quality is critical for implementing public policies that can limit anthropogenic emissions, reduce human exposure and allow for preparation and interventions in the health sector. In Brazil, wildfires constitute an important source of particulate matter emission, particularly in the country’s northern and midwestern regions, areas that are under-served in terms of air quality monitoring infrastructure. In the absence of regulatory-grade monitoring networks, low-cost sensors offer a viable alternative for generating real-time, publicly available estimates of pollutant concentrations. Here, we examine data from two low-cost sensors deployed in Brasília, in the Federal District of Brazil, during the 2022 wildfire season and use NOAA’s HYSPLIT model to investigate the origin of a particulate matter peak detected by the sensors. There was high agreeability of the data from the two sensors, with the raw values showing that daily average PM2.5 concentrations reached peak values of 46 µg/m3 and 43 µg/m3 at the school and park sites, respectively. This study demonstrates the value of low-cost sensors and their possible application in real-time scenarios for environmental health surveillance purposes.

Use of Low-Cost Sensors for Environmental Health Surveillance: Wildfire-Related Particulate Matter Detection in Brasília, Brazil

A new strategy for risk assessment of PM2.5-bound elements by considering the influence of wind regimes.

Green areas provide numerous ecosystem services (ES) that are essential for human well-being, such as climate regulation, air quality regulation, disease regulation, and recreational opportunities. In this study, we assessed the ecosystem services provided by green areas and their implications for human health in Brazil. Considering emerging problems in Brazil, such as population growth, the health crisis, and the increase in deforestation, ES mapping is essential to understand barriers and diagnose strategies for promoting the health and well-being of the Brazilian population. Using remote sensing data and geographic information systems, we evaluated the Green Areas Ecosystem Services (GAES), composed of i) the provision of green areas; ii) regulation of air quality; iii) climate regulation; iv) diseases regulation (cardiorespiratory); and v) cultural services, including recreation, sports, and ecotourism. Our findings suggest that green areas in Brazil provide a considerable amount of ecosystem services that are relevant to human health. Over 70 % of Brazil exhibited GAES values exceeding 0.5 (relative scale ranging from 0 to 1). This indicates that a significant portion of the Brazilian population has access to green spaces that provide important services, such as air and water purification, climate regulation, and disease regulation. The mean GAES value for the entire country was 0.78, with notable regional variations. The highest GAES was found in regions dominated by the Amazon Forest (GAES = 0.81), while the smallest offers of GAES are in the northeast (GAES = 0.40) and south (GAES = 0.41) regions of the country The type of vegetation was an important factor in the regulation of climate and air quality. However, factors such as population density and urbanization interfere with the regulation of diseases. Considering the 10 states with the highest and lowest per capita income and population density, the state of Rio Grande do Sul, located in the South region, had the highest mean GAES value; while the state of Acre, in the North region, had the lowest. Our findings suggest that interventions to improve green area provision and quality may be most effective in the northeast and South regions of Brazil. This is indicative of the observed lower GAES provision in these regions, primarily attributed to elevated urbanization levels leading to the conversion of green areas into urban zones. Overall, our study highlights the importance of green areas for human well-being and provides valuable information for policymakers to prioritize interventions to improve GAES provision across Brazil. 

Ecosystem services provided by green areas and their implications for human health in Brazil

Forest fires cause many environmental impacts, including air pollution. Brazil is a very fire-prone region where few studies have investigated the impact of wildfires on air quality and health. We proposed to test two hypotheses in this study: i) the wildfires in Brazil have increased the levels of air pollution and posed a health hazard in 2003–2018, and ii) the magnitude of this phenomenon depends on the type of land use and land cover (e.g., forest area, agricultural area, etc.). Satellite and ensemble models derived data were used as input in our analyses. Wildfire events were retrieved from Fire Information for Resource Management System (FIRMS), provided by NASA; air pollution data from the Copernicus Atmosphere Monitoring Service (CAMS); meteorological variables from the ERA-Interim model; and land use/cover data were derived from pixel-based classification of Landsat satellite images by MapBiomas. We used a framework that infers the “wildfire penalty” by accounting for differences in linear pollutant annual trends (β) between two models to test these hypotheses. The first model was adjusted for Wildfire-related Land Use activities (WLU), considered as an adjusted model. In the second model, defined as an unadjusted model, we removed the wildfire variable (WLU). Both models were controlled by meteorological variables. We used a generalized additive approach to fit these two models. To estimate mortality associated with wildfire penalties, we applied health impact function. Our findings suggest that wildfire events between 2003 and 2018 have increased the levels of air pollution and posed a significant health hazard in Brazil, supporting our first hypothesis. For example, in the Pampa biome, we estimated an annual wildfire penalty of 0.005 μg/m3 (95%CI: 0.001; 0.009) on PM2.5. Our results also confirm the second hypothesis. We observed that the greatest impact of wildfires on PM2.5 concentrations occurred in soybean areas in the Amazon biome. During the 16 years of the study period, wildfires originating from soybean areas in the Amazon biome were associated with a total penalty of 0.64 μg/m3 (95%CI: 0.32; 0.96) on PM2.5, causing an estimated 3872 (95%CI: 2560; 5168) excess deaths. Sugarcane crops were also a driver of deforestation-related wildfires in Brazil, mainly in Cerrado and Atlantic Forest biomes. Our findings suggest that between 2003 and 2018, fires originating from sugarcane crops were associated with a total penalty of 0.134 μg/m3 (95%CI: 0.037; 0.232) on PM2.5 in Atlantic Forest biome, resulting in an estimated 7600 (95%CI: 4400; 10,800) excess deaths during the study period, and 0.096 μg/m3 (95%CI: 0.048; 0.144) on PM2.5 in Cerrado biome, resulting in an estimated 1632 (95%CI: 1152; 2112) excess deaths during the study period. Considering that the wildfire penalties observed during our study period may continue to be a challenge in the future, this study should be of interest to policymakers to prepare future strategies related to forest protection, land use management, agricultural activities, environmental health, climate change, and sources of air pollution. 

The impact of wildfires on air pollution and health across land use categories in Brazil over a 16-year period.

The impact of long-term weather changes on air quality in Brazil

Corrigendum to “The impact of long-term weather changes on air quality in Brazil” [J. Atmos. Environ. 283 (2022) 119182]

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The impact of wildfires on air pollution and health across land use categories in Brazil over a 16-year period.

The impact of long-term weather changes on air quality in Brazil

Corrigendum to “The impact of long-term weather changes on air quality in Brazil” [J. Atmos. Environ. 283 (2022) 119182]