scholarly journals Characterization and Trends of Fine Particulate Matter (PM2.5) Fire Emissions in the Brazilian Cerrado during 2002–2017

2019 ◽  
Vol 11 (19) ◽  
pp. 2254 ◽  
Author(s):  
Guilherme Augusto Verola Mataveli ◽  
Maria Elisa Siqueira Silva ◽  
Daniela de Azeredo França ◽  
Nathaniel Alan Brunsell ◽  
Gabriel de Oliveira ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Land Cover ◽  
Anthropogenic Activities ◽  
Fine Particulate Matter ◽  
Grid Cell ◽  
Northern Region ◽  
Brazilian Cerrado ◽  
Annual Average ◽  
Fire Emissions ◽  
Moderate Resolution Imaging Spectroradiometer

Fire occurrence is a major disturbance in the Brazilian Cerrado, which is driven by both natural and anthropogenic activities. Despite increasing efforts for monitoring the Cerrado, a biome-scale study for quantifying and understanding the variability of fire emissions is still needed. We aimed at characterizing and finding trends in Particulate Matter with diameter less than 2.5 µm (PM2.5) fire emissions in the Brazilian Cerrado using the PREP-CHEM-SRC emissions preprocessing tool and Moderate Resolution Imaging Spectroradiometer (MODIS) active fires datasets for the 2002–2017 period. Our results showed that, on average, the Cerrado emitted 1.08 Tg year−1 of PM2.5 associated with fires, accounting for 25% and 15% of the PM2.5 fire emissions in Brazil and South America, respectively. Most of the PM2.5 fire emissions were concentrated in the end of the dry season (August, 0.224 Tg month−1 and September, 0.386 Tg month−1) and in the transitional month (October, 0.210 Tg month−1). Annually, 66% of the total emissions occurred over the savanna land cover; however, active fires that were detected in the evergreen broadleaf land cover tended to emit more than active fires occurring in the savanna land cover. Spatially, each 0.1° grid cell emitted, on average, 0.5 Mg km−2 year−1 of PM2.5 associated with fires, but the values can reach to 16.6 Mg km−2 year−1 in a single cell. Higher estimates of PM2.5 emissions associated with fires were mostly concentrated in the northern region, which is the current agricultural expansion frontier in this biome. When considering the entire Cerrado, we found an annual decreasing trend representing -1.78% of the annual average PM2.5 emitted from fires during the period analyzed, however, the grid cell analysis found annual trends representing ± 35% of the annual average PM2.5 fire emissions.

scholarly journals Exploring the Use of PlanetScope Data for Particulate Matter Air Quality Research

2021 ◽  
Vol 13 (15) ◽  
pp. 2981
Author(s):  
Jeanné le Roux ◽  
Sundar Christopher ◽  
Manil Maskey
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Land Cover ◽  
Spectral Response ◽  
Fine Particulate Matter ◽  
Daily Basis ◽  
Land Cover Types ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
The Difference ◽  
Geolocation Accuracy

Planet, a commercial company, has achieved a key milestone by launching a large fleet of small satellites (smallsats) that provide high spatial resolution imagery of the entire Earth’s surface on a daily basis with its PlanetScope sensors. Given the potential utility of these data, this study explores the use for fine particulate matter (PM2.5) air quality applications. However, before these data can be utilized for air quality applications, key features of the data, including geolocation accuracy, calibration quality, and consistency in spectral signatures, need to be addressed. In this study, selected Dove-Classic PlanetScope data is screened for geolocation consistency. The spectral response of the Dove-Classic PlanetScope data is then compared to Moderate Resolution Imaging Spectroradiometer (MODIS) data over different land cover types, and under varying PM2.5 and mid visible aerosol optical depth (AOD) conditions. The data selected for this study was found to fall within Planet’s reported geolocation accuracy of 10 m (between 3–4 pixels). In a comparison of top of atmosphere (TOA) reflectance over a sample of different land cover types, the difference in reflectance between PlanetScope and MODIS ranged from near-zero (0.0014) to 0.117, with a mean difference in reflectance of 0.046 ± 0.031 across all bands. The reflectance values from PlanetScope were higher than MODIS 78% of the time, although no significant relationship was found between surface PM2.5 or AOD and TOA reflectance for the cases that were studied. The results indicate that commercial satellite data have the potential to address Earth-environmental issues.

scholarly journals The impact of US wildland fires on ozone and particulate matter: a comparison of measurements and CMAQ model predictions from 2008 to 2012

2018 ◽  
Vol 27 (10) ◽  
pp. 684 ◽  
Author(s):  
Joseph L. Wilkins ◽  
George Pouliot ◽  
Kristen Foley ◽  
Wyat Appel ◽  
Thomas Pierce
Keyword(s):  
Particulate Matter ◽  
Air Quality ◽  
Wildland Fire ◽  
Fine Particulate Matter ◽  
Model Performance ◽  
Grid Cell ◽  
Emissions Inventory ◽  
Fire Emissions ◽  
The Mean ◽  
The Impact

Wildland fire emissions are routinely estimated in the US Environmental Protection Agency’s National Emissions Inventory, specifically for fine particulate matter (PM2.5) and precursors to ozone (O3); however, there is a large amount of uncertainty in this sector. We employ a brute-force zero-out sensitivity method to estimate the impact of wildland fire emissions on air quality across the contiguous US using the Community Multiscale Air Quality (CMAQ) modelling system. These simulations are designed to assess the importance of wildland fire emissions on CMAQ model performance and are not intended for regulatory assessments. CMAQ ver. 5.0.1 estimated that fires contributed 11% to the mean PM2.5 and less than 1% to the mean O3 concentrations during 2008–2012. Adding fires to CMAQ increases the number of ‘grid-cell days’ with PM2.5 above 35 µg m−3 by a factor of 4 and the number of grid-cell days with maximum daily 8-h average O3 above 70 ppb by 14%. Although CMAQ simulations of specific fires have improved with the latest model version (e.g. for the 2008 California wildfire episode, the correlation r = 0.82 with CMAQ ver. 5.0.1 v. r = 0.68 for CMAQ ver. 4.7.1), the model still exhibits a low bias at higher observed concentrations and a high bias at lower observed concentrations. Given the large impact of wildland fire emissions on simulated concentrations of elevated PM2.5 and O3, improvements are recommended on how these emissions are characterised and distributed vertically in the model.

scholarly journals Impacts of historical climate and land cover changes on fine particulate matter (PM<sub>2.5</sub>) air quality in East Asia over 1980–2010

2016 ◽  
Author(s):  
Yu Fu ◽  
Amos P. K. Tai ◽  
Hong Liao
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Particulate Matter ◽  
Air Quality ◽  
Land Cover ◽  
East Asia ◽  
Fine Particulate Matter ◽  
Anthropogenic Emissions ◽  
Voc Emissions ◽  
Fine Particulate

Abstract. To examine the effects of changes in climate, land cover and land use (LCLU), and anthropogenic emissions on fine particulate matter (PM2.5) between the 5-year periods 1981–1985 and 2007–2011 in East Asia, we perform a series of simulations using a global chemical transport model (GEOS-Chem) driven by assimilated meteorological data and a suite of land cover and land use data. Our results indicate that climate change alone could lead to a decrease in wintertime PM2.5 concentration by 4.0–12.0 μg m−3 in northern China, but an increase in summertime PM2.5 by 6.0–8.0 μg m−3 in those regions. These changes are attributable to the changing chemistry and transport of all PM2.5 components driven by long-term trends in temperature, wind speed and mixing depth. The concentration of secondary organic aerosol (SOA) is simulated to increase by 0.2–0.8 μg m−3 in both summer and winter in most regions of East Asia due to climate change alone, mostly reflecting higher biogenic volatile organic compound (VOC) emissions under warming. The impacts of LCLU change alone on PM2.5 (−2.1 to +1.3 μg m−3) are smaller than that of climate change, but among the various components the sensitivity of SOA and thus organic carbon to LCLU change (−0.4 to +1.2 μg m−3) is quite significant especially in summer, which is driven mostly by changes in biogenic VOC emissions following cropland expansion and changing vegetation density. The combined impacts show that while the effect of climate change on PM2.5 air quality is more pronounced, LCLU change could offset part of the climate effect in some regions but exacerbate it in others. As a result of both climate and LCLU changes combined, PM2.5 levels are estimated to change by −12.0 to +12.0 μg m−3 across East Asia between the two periods. Changes in anthropogenic emissions remain the largest contributor to deteriorating PM2.5 air quality in East Asia during the study period, but climate and LCLU changes could lead to a substantial modification of PM2.5 levels.

scholarly journals Spatial and temporal variability of sources of ambient fine particulate matter (PM<sub>2.5</sub>) in California

2014 ◽  
Vol 14 (22) ◽  
pp. 12085-12097 ◽  
Author(s):  
S. Hasheminassab ◽  
N. Daher ◽  
A. Saffari ◽  
D. Wang ◽  
B. D. Ostro ◽  
...  
Keyword(s):  
Particulate Matter ◽  
Biomass Burning ◽  
Total Mass ◽  
Fine Particulate Matter ◽  
The State ◽  
Vehicular Emissions ◽  
San Jose ◽  
Annual Average ◽  
Fine Particulate ◽  
Sampling Locations

Abstract. To identify major sources of ambient fine particulate matter (PM2.5, dp < 2.5 μm) and quantify their contributions in the state of California, a positive matrix factorization (PMF) receptor model was applied on Speciation Trends Network (STN) data, collected between 2002 and 2007 at eight distinct sampling locations, including El Cajon, Rubidoux, Los Angeles, Simi Valley, Bakersfield, Fresno, San Jose, and Sacramento. Between five to nine sources of fine PM were identified at each sampling site, several of which were common among multiple locations. Secondary aerosols, including secondary ammonium nitrate and ammonium sulfate, were the most abundant contributor to ambient PM2.5 mass at all sampling sites, except for San Jose, with an annual average cumulative contribution of 26 to 63%, across the state. On an annual average basis, vehicular emissions (including both diesel and gasoline vehicles) were the largest primary source of fine PM at all sampling sites in southern California (17–18% of total mass), whereas in Fresno and San Jose, biomass burning was the most dominant primary contributor to ambient PM2.5 (27 and 35% of total mass, respectively), in general agreement with the results of previous source apportionment studies in California. In Bakersfield and Sacramento, vehicular emissions and biomass burning displayed relatively equal annual contributions to ambient PM2.5 mass (12 and 25%, respectively). Other commonly identified sources at all sites included aged and fresh sea salt and soil, which contributed to 0.5–13%, 2–27%, and 1–19% of the total mass, respectively, across all sites and seasons. In addition, a few minor sources were identified exclusively at some of the sites (e.g., chlorine sources, sulfate-bearing road dust, and different types of industrial emissions). These sources overall accounted for a small fraction of the total PM mass across the sampling locations (1 to 15%, on an annual average basis).

scholarly journals US particulate matter air quality improves except in wildfire-prone areas

2018 ◽  
Vol 115 (31) ◽  
pp. 7901-7906 ◽  
Author(s):  
Crystal D. McClure ◽  
Daniel A. Jaffe
Keyword(s):  
United States ◽  
Particulate Matter ◽  
Fine Particulate Matter ◽  
The United States ◽  
Total Carbon ◽  
Positive Trend ◽  
Modis Aod ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Using Data

Using data from rural monitoring sites across the contiguous United States, we evaluated fine particulate matter (PM2.5) trends for 1988–2016. We calculate trends in the policy-relevant 98th quantile of PM2.5 using Quantile Regression. We use Kriging and Gaussian Geostatistical Simulations to interpolate trends between observed data points. Overall, we found positive trends in 98th quantile PM2.5 at sites within the Northwest United States (average 0.21 ± 0.12 µg·m−3·y−1; ±95% confidence interval). This was in contrast with sites throughout the rest of country, which showed a negative trend in 98th quantile PM2.5, likely due to reductions in anthropogenic emissions (average −0.66 ± 0.10 µg·m−3·y−1). The positive trend in 98th quantile PM2.5 is due to wildfire activity and was supported by positive trends in total carbon and no trend in sulfate across the Northwest. We also evaluated daily moderate resolution imaging spectroradiometer (MODIS) aerosol optical depth (AOD) for 2002–2017 throughout the United States to compare with ground-based trends. For both Interagency Monitoring of Protected Visual Environments (IMPROVE) PM2.5 and MODIS AOD datasets, we found positive 98th quantile trends in the Northwest (1.77 ± 0.68% and 2.12 ± 0.81% per year, respectively) through 2016. The trend in Northwest AOD is even greater if data for the high-fire year of 2017 are included. These results indicate a decrease in PM2.5 over most of the country but a positive trend in the 98th quantile PM2.5 across the Northwest due to wildfires.

scholarly journals Impacts of historical climate and land cover changes on fine particulate matter (PM<sub>2.5</sub>) air quality in East Asia between 1980 and 2010

2016 ◽  
Vol 16 (16) ◽  
pp. 10369-10383 ◽  
Author(s):  
Yu Fu ◽  
Amos P. K. Tai ◽  
Hong Liao
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Particulate Matter ◽  
Air Quality ◽  
Land Cover ◽  
East Asia ◽  
Fine Particulate Matter ◽  
Anthropogenic Emissions ◽  
Voc Emissions ◽  
Fine Particulate

Abstract. To examine the effects of changes in climate, land cover and land use (LCLU), and anthropogenic emissions on fine particulate matter (PM2.5) between the 5-year periods 1981–1985 and 2007–2011 in East Asia, we perform a series of simulations using a global chemical transport model (GEOS-Chem) driven by assimilated meteorological data and a suite of land cover and land use data. Our results indicate that climate change alone could lead to a decrease in wintertime PM2.5 concentration by 4.0–12.0 µg m−3 in northern China, but to an increase in summertime PM2.5 by 6.0–8.0 µg m−3 in those regions. These changes are attributable to the changing chemistry and transport of all PM2.5 components driven by long-term trends in temperature, wind speed and mixing depth. The concentration of secondary organic aerosol (SOA) is simulated to increase by 0.2–0.8 µg m−3 in both summer and winter in most regions of East Asia due to climate change alone, mostly reflecting higher biogenic volatile organic compound (VOC) emissions under warming. The impacts of LCLU change alone on PM2.5 (−2.1 to +1.3 µg m−3) are smaller than that of climate change, but among the various components the sensitivity of SOA and thus organic carbon to LCLU change (−0.4 to +1.2 µg m−3) is quite significant especially in summer, which is driven mostly by changes in biogenic VOC emissions following cropland expansion and changing vegetation density. The combined impacts show that while the effect of climate change on PM2.5 air quality is more pronounced, LCLU change could offset part of the climate effect in some regions but exacerbate it in others. As a result of both climate and LCLU changes combined, PM2.5 levels are estimated to change by −12.0 to +12.0 µg m−3 across East Asia between the two periods. Changes in anthropogenic emissions remain the largest contributor to deteriorating PM2.5 air quality in East Asia during the study period, but climate and LCLU changes could lead to a substantial modification of PM2.5 levels.

scholarly journals Burden of cardiovascular diseases associated with fine particulate matter in Beijing, China: an economic modelling study

2020 ◽  
Vol 5 (10) ◽  
pp. e003160
Author(s):  
Yawen Jiang ◽  
Shan Jiang ◽  
Weiyi Ni
Keyword(s):  
Particulate Matter ◽  
Cardiovascular Diseases ◽  
Fine Particulate Matter ◽  
Ambient Air ◽  
Medical Costs ◽  
Economic Modelling ◽  
Annual Average ◽  
Fine Particulate ◽  
Life Years ◽  
Qaly Loss

ObjectiveTo evaluate the economic and humanistic burden associated with cardiovascular diseases that were attributable to fine particulate matter (≤ 2.5 μg/m3 in aerodynamic diameter; PM2.5) in Beijing.MethodsThis study used a health economic modelling approach to compare the actual annual average PM2.5 concentration with the PM2.5 concentration limit (35 µg/m3) as defined by the Chinese Ambient Air Quality Standard in terms of cardiovascular disease outcomes in Beijing adult population. The outcomes included medical costs, quality-adjusted life-years (QALYs) and net monetary loss (NML). Beijing annual average PM2.5 concentration was around 105 µg/m3 during 2013–2015. Therefore, we estimated the differences in cardiovascular outcomes of Beijing adults between exposure to the PM2.5 concentration of 105 µg/m3 and exposure to the concentration of 35 µg/m3. According to WHO estimates, the hazard ratios of coronary heart disease and stroke associated with the increase of PM2.5 concentration from 35 to 105 µg/m3 were 1.15 and 1.29, respectively.ResultsThe total 1-year excess medical costs of cardiovascular diseases associated with PM2.5 pollution in Beijing was US$147.9 million and the total 1-year QALY loss was 92 574 in 2015, amounting to an NML of US$2281.8 million. The expected lifetime incremental costs for a male Beijing adult and a female Beijing adult were US$237 and US$163, the corresponding QALY loss was 0.14 and 0.12, and the corresponding NML was US$3514 and US$2935.ConclusionsPM2.5-related cardiovascular diseases imposed high economic and QALY burden on Beijing society. Continuous and intensive investment on reducing PM2.5 concentration is warranted even when only cardiovascular benefits are considered.

scholarly journals Evaluating the influence of land use and land cover change on fine particulate matter

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Wei Yang ◽  
Xiaoli Jiang
Keyword(s):  
Land Use ◽  
Particulate Matter ◽  
Land Cover ◽  
Land Cover Change ◽  
Fine Particulate Matter ◽  
Influence Factors ◽  
Low Grade ◽  
Geographically Weighted Regression Model ◽  
Fine Particulate ◽  
The Impact

AbstractFine particulate matter (i.e. particles with diameters smaller than 2.5 microns, PM2.5) has become a critical environmental issue in China. Land use and land cover (LULC) is recognized as one of the most important influence factors, however very fewer investigations have focused on the impact of LULC on PM2.5. The influences of different LULC types and different land use and land cover change (LULCC) types on PM2.5 are discussed. A geographically weighted regression model is used for the general analysis, and a spatial analysis method based on the geographic information system is used for a detailed analysis. The results show that LULCC has a stable influence on PM2.5 concentration. For different LULC types, construction lands have the highest PM2.5 concentration and woodlands have the lowest. The order of PM2.5 concentration for the different LULC types is: construction lands > unused lands > water > farmlands >grasslands > woodlands. For different LULCC types, when high-grade land types are converted to low-grade types, the PM2.5 concentration decreases; otherwise, the PM2.5 concentration increases. The result of this study can provide a decision basis for regional environmental protection and regional ecological security agencies.

scholarly journals Assessment of air quality within Maiganga coal mining area in Akko Local Government Area, Gombe State, Nigeria

2020 ◽  
Vol 4 (3) ◽  
pp. 001-012
Author(s):  
Ademu Tanko Ogah ◽  
Obaje Daniel Opaluwa ◽  
Mohammed Alkali ◽  
Kumo Lass
Keyword(s):  
Particulate Matter ◽  
Volatile Organic Compounds ◽  
Organic Compounds ◽  
Anthropogenic Activities ◽  
Fine Particulate Matter ◽  
Environmental Standards ◽  
Criteria Air Pollutants ◽  
Fine Particulate ◽  
Volatile Organic ◽  
Coarse Particulate Matter

Anthropogenic activity especially coal mining contributes immensely to environmental pollution within coalmine and the host community especially if not well managed. This study is on the assessment of air quality in and around Maiganga coalmine, with the objectives of finding out the ambient concentration levels of criteria air pollutants within the coalmine, the Maiganga community and the four control sites 2km north, south, east and west of the coalmine, as well as compare the findings with the concentration levels of pollutants recommended as acceptable safety limits set by Federal Ministry of Environment, FMEnv. Six sampling locations were selected for detail assessment, with one point in each of the sites mentioned. Measurement of concentrations of criteria air pollutants; sulphur dioxide (SO2), nitrogen dioxide (NO2) volatile organic compounds (VOCs), carbon monoxide (CO), ammonia (NH3), and ozone (O3) were taken in-situ using Personal Toxic Gas Monitor (Tango TXI single gas monitor). Fine particulate matter (PM2.5), coarse particulate matter (PM10), were collected using a Portable Counter HT – 9601 (PM2.5 and PM10) personal dust meter high volume gravity sampler. Volatile organic compounds (VOCs) were also measured using a Portable Hand Held Gas Detector (Porcheck+). The study was done during the dry season and the results revealed that, coarse paticulate matter (PM10) was above the stipulated safety limit of 250µg/m3 set by the FMEnv for the coal mine area and Maiganga community but all other parameters were within the safety limits of the FMEnv. CO, NO2, SO2, and NH3 in coalmine area had concentrations lower than in that in control areas because of other anthropogenic activities like burning, heating, waste disposal, agricultural practices and a host of others taking place in the control area and which are not available in the coalmine area. However, the concentrations of the aforementioned parameters were higher in Maiganga community than in the control areas due to higher rate of anthropogenic activities in the community than in the control areas. The hypothesis were tested using student t – test, and the alternative hypothesis was accepted which showed there was no significant variations in the values of fine particulate matter (PM2.5), coarse particulate matter (PM10), sulphur dioxide (SO2), nitrogen dioxide (NO2), volatile organic compounds (VOCs), carbon monoxide (CO), ammonia (NH3), and ozone (O3) obtain from the coalmine, Maiganga community and the Control (N.S.E.W) with safety limits set by FMEnv. It is however, recommended that the Federal Ministry of Environment and National Environmental Standards and Regulations Enforcement Agency (NESREA) should ensure strict compliance with safety and environmental standards agreed upon during Environmental Impact Assessment (EIA).

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