Particulate Matter Concentrations Research Articles

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.

Evaluation of the PM2.5 concentrations in South America: Climatological patterns and trend analysis

This study assessed the concentration of particulate matter with an aerodynamic diameter of 2.5 (PM2.5) over South America (SA) based on climatological patterns and trend analysis. This study used monthly PM2.5 data from the Copernicus Atmosphere Monitoring Service (CAMS) at the European Centre for Medium-range Weather Forecasts from 2003 to 2022. The bilinear interpolation method was applied to the data resampling from 0.75° × 0.75°–0.25° × 0.25° spatial resolution, and subsequently, the climatological analysis was performed on seasonal and annual scales of PM2.5 concentrations for the 20-year series. The assessment comprised three main stages: 1) descriptive statistics, 2) seasonal and annual climatology patterns, and 3) trend analysis (Mann-Kendall - MK and Pettitt tests). Results indicated that the largest annual PM2.5 concentrations were found in the Amazon region and northern Paraguay due the El-Niño South Oscillation events (2003–2005, 2007, 2010, 2020, and 2022). The annual average PM2.5 concentrations exceeded the WHO recommended limit (5 μg m−3), ranging from 15.57 μg m−3 (1999) and 22.74 μg m−3 (2007 and 2010). The highest PM2.5 concentrations were observed in the Amazon and Chile (Santiago), reaching 160.4 μg m−3 annually and 177.8 μg m−3 seasonally (spring). Elevated seasonal PM2.5 concentrations were attributed to increased deforestation and wildfires associated with meteorological systems such as the Bolivian high and subtropical jets during dry periods (winter and spring). The MK test revealed a significant reduction in PM2.5 concentrations between 2003 and 2022, observed in Argentina (north), Brazil (arc of reforestation), Bolivia (south), and Chile (north). Reduction values varied between 0.5 and 10 μg m−3.year−1 annually and during winter, attributed to no-tillage practices in regions cultivating commodities. The Pettitt test also identified significant structural changes occurring in 2006–2008 and 2010–2011, aligning with areas highlighted in the MK test. This study provides valuable insights for air quality and environmental monitoring managers to mitigate PM2.5 pollution in SA.

Particulate matter in necropsy activities: experience from a health operators’ exposure monitoring campaign

BackgroundOperators in the obituary and necropsy sectors are exposed to various environmental hazards during specific tasks. Despite this exposure, occupational risks have often been underestimated, resulting in a lack of substantial evidence. The primary objectives of this study were to identify sources of chemical risk, establish procedures for monitoring and quantifying exposure during necropsy activities, and recommend adjustments to regulatory guidelines to protect the health of the operators. The study was conducted at the Legal Medicine Unit of the Umberto I General Hospital in Rome, focusing on the quantitative measurement of particulate matter (PM) exposure among at-risk operators during necropsy activities. Environmental levels of total suspended particles, PM10, PM4, PM2.5, and PM1 were assessed by evaluating the average, minimum, and maximum instantaneous indoor concentrations using an airborne analyzer.ResultsThe monitoring activities revealed that the PM concentrations were significantly lower than the recognized reference values. However, bone sawing, body removal, and cleaning were identified as high-risk maneuvers for dust suspension.ConclusionsOur study highlighted specific risks associated with necropsy activities, particularly concerning timing and certain maneuvers. These results may lead to interventions for improving current prevention procedures, implementing good practices, and developing specific guidelines to enhance operator safety.

A pilot study on a 30 t/h biomass gasification-combustion plant

As a renewable energy with zero carbon emission, the utilization of biomass has attracted widely studied. One of the most effective methods is to gasify the biomass into high-quality gas fuel. In the recent years, the majority of research on biomass gasification is conducted in the laboratory. However, it lacks the research in engineering application scale. In this work, a biomass gasification-combustion plant was designed and built to provide the industrial steam with a rate of 30 t/h for a food industrial park. The agricultural and forestry waste biomass was gasified in a gasifier, and then the product gas combusted in a boiler to supply the steam. The characteristics of the product gas from the gasifier were studied. The corrosion and pollutants in the combustion process were investigated. In the gasification process, the main components of the product gas are CO, H2 and CH4. CO and H2 account for 29.55 vol%-30.56 vol% and 11.65 vol%-15.35 vol%, respectively. The calorific value of the product gas is 5.88–6.29 MJ/m3. The tar concentration is 110.58–155.07 g/Nm3. At the outlet of the boiler, the concentration of the filterable particulate matter is 300.25 mg/Nm3, and the particle size is concentrated at 1.00–2.50 μm. The concentration of the condensable particulate matter (CPM) is 157.14 mg/Nm3, and the proportion of water-soluble ions in CPM is 86.36 wt%. The concentration of Cl−, SO42-, NH4+ and Na+ in CPM is relatively high, with the values of 28.83 mg/Nm3, 10.29 mg/Nm3, 7.46 mg/Nm3, and 5.06 mg/Nm3, respectively. During the half-year running, the ash deposition and corrosion were detected in the boiler heating surface and the economizer. The ash deposit in the boiler is mainly composed of the sulfate and silicate, such as CaSO4, Zn2SO4, Na2SO4 and K3Na(SO4)2. The ash deposit in the economizer is primarily composed of the sulfate and a small amount of alkali metal chloride. The flue gas reaches the emission requirement after passing through the pollution control devices and can be discharged into the atmosphere.

Characterization of carbonaceous components and PAHs on ultrafine particles in Phnom Penh, Cambodia.

This study investigated seasonal fluctuations in particulate matter (PM) concentrations, including carbon and polycyclic aromatic hydrocarbon (PAH) components, in Phnom Penh, Cambodia, focusing on ultrafine particles (UFPs or ≤ 100nm). UFP levels were notably higher during the dry season, averaging 23.73 ± 3.7µg/m3 compared to 19.64 ± 3.4µg/m3 in the wet season, attributed to increased emissions from vehicles and agricultural burning. In contrast, lower concentrations during the wet season were due to scavenging effect of rain. When compared to other Southeast Asian cities, UFP levels in Phnom Penh were significantly higher during the dry season, surpassing those in cities like Bangkok and Kuala Lumpur. Seasonal variations in carbonaceous components showed higher elemental carbon (EC) and total carbon (TC) during the dry season, with EC/TC ratios suggesting substantial influence from vehicular emissions and biomass burning. PAH analysis revealed seasonal disparities, with higher concentrations of benzo[b]fluoranthene (BbF) and benzo[k]fluoranthene (BkF) during the wet season, whereas fluoranthene (Flu) and pyrene (Pyr) were consistently present, indicating diverse PAH sources. The Flu/(Flu + Pyr) ratios, indicative of biomass burning, were higher in the dry season. Correlations between PAHs and carbon components confirmed combustion as a significant source of PAHs, aligning with global trends. This emphasizes the need to address distinct PM sources during various season in Phnom Penh.

Research on characteristics and influencing factors of road dust emission in a southern city in China.

One of the primary causes of urban atmospheric particulate matter, which is harmful to human health in addition to affecting air quality and atmospheric visibility, is road dust. This study used online monitoring equipment to examine the characteristics of road dust emissions, the effects of temperature, humidity, and wind speed on road dust, as well as the correlation between road and high-space particulate matter concentrations. A section of a real road in Jinhua City, South China, was chosen for the study. The findings demonstrate that the concentration of road dust particles has a very clear bimodal single-valley distribution throughout the day, peaking between 8:00 and 11:00 and 19:00 and 21:00 and troughing between 14:00 and 16:00. Throughout the year, there is a noticeable seasonal change in the concentration of road dust particles, with the highest concentration in the winter and the lowest in the summer. Simultaneously, it has been discovered that temperature and wind speed have the most effects on particle concentration. The concentration of road dust particles reduces with increasing temperature and wind speed. The particle concentrations of road particles and those from urban environmental monitoring stations have a strong correlation, although the trend in the former is not entirely consistent, and the changes in the former occur approximately 1 h after the changes in the latter.

Exposure to ultrafine particles, black carbon and particulate matter during commute in a suburb from the Yangtze River Delta, China

This study evaluated the exposure of commuters to particulate matter (PM), black carbon (BC), and ultrafine particulate matter (UFP) concentrations in five different traffic microenvironments (bike, bus, taxi, electric motorbike, and subway) under various conditions, such as regular and dust days, weekdays and weekends, and peak and off-peak commute hours in Nanjing, China. In the morning peak hours, bicycle commuters were exposed to the highest PM concentration, those on buses to the highest BC concentration (3.4 ± 3.0 μg/m3), and those on buses and taxis to the highest UFP number concentration. Throughout the rides, the commuter on the subway had the lowest mean exposure concentration of PM, BC, and UFP number. Bicycle commuters (16.25 μg/km) had the highest total inhaled dose of PM2.5, followed by e-bikers (1.98 μg/km), bus riders (1.28 μg/km), taxi riders (0.69 μg/km), and subway users (0.45 μg/km). Weekday PM2.5 exposure levels (115 μg/m3) and BC exposure levels (1.8 μg/m3) were higher than weekend levels (170% and 158%, respectively). The mean exposure concentration of PM10 (1299 ± 1286 μg/m3) in the evening peak of dust days was 803% and 994% higher than the mean concentrations on weekdays and holidays, respectively. PM2.5, PM10, and BC concentrations on dust days were significantly higher than those on weekdays and holidays. The overall mean ratios of PM1/PM2.5 and PM2.5/PM10 were 0.47 and 0.36, respectively, and the five commuting microenvironments had higher proportions of 2.5–10 μm and 1–2.5 μm particles in PM10 and PM2.5, respectively. Reducing the sources of particulate matter in the corresponding particle size ranges could lower exposure levels.

The evolution of tire-road wear particles and road surface texture under rolling friction

Traffic-related non-exhaust emissions are an important part of air pollution, which can adversely affect human health when inhaled. Tire-road wear is a significant source of these emissions and originates from tire-road friction. To gain a deeper understanding of the relationship between tire-road wear particles and road surface texture under rolling friction, this study conducted long-term durability experiments using a Model Mobile Load Simulator at 1/3rd scale to form a closed environmental test system. The experiments were conducted under 30°C, 50 % relative humidity, 0.7 MPa tire-ground pressure, and 5.4 km/h rolling speed. Based on an analysis of asphalt concrete-13 Marshall samples’ British Pendulum Number (BPN) value, Mean Texture Depth (MTD), wear particle size distribution, particulate matter (PM) concentration, and thermogravimetric analysis during 1600,000 rolling times, this study draws the following conclusions: This indoor research has indicated that the weight ratio of tire and asphalt wear to aggregates and mineral fillers is approximately 4.5:5.5 (after stabilization). When the tire contacts the aggregate exposed after asphalt film peeling, it significantly increases PM10 concentration. Under the rolling friction of the tire-road contact, the quality loss of asphalt concrete follows an exponential decay curve with an R2 of 0.99. Road (asphalt concrete pavement) wear per square meter of tire-road contact was 5.32×10^−4 g and 2.13×10^−4 g (before and after asphalt film peeling). It is hoped that this study will contribute to the field of tire-road wear, including non-exhaust emissions, and provide methods and theoretical support for mitigating re-suspension dust.

Analyzing Research on Air Quality Modeling in the Indian Setting: A Thorough Overview

India, being a developing nation, need efficient strategies to mitigate air pollution in order to prevent premature deaths of numerous individuals. Air quality models not only give data on the concentrations of air pollution, but also offer valuable knowledge about its sources. Prior research on air quality modelling conducted in India at the local and regional levels. This present study aims to evaluate the comprehensive grasp of the existing gaps and to explore potential future possibilities. The meticulously recorded studies conducted in various regions of India during the previous decade, employing systematic searches on various databases like Google Scholar and Google. The majority of air quality research mostly centers on megacities, disregarding the smaller cities that also require substantial attention in the future. There were very few research that were primarily focused on the central area of India, even though the majority of modelling studies were conducted in that region. Upon reviewing both local and regional numerical models, it became evident that there is a requirement for improved emission inputs. Furthermore, the statistical models have shown that it is important to meticulously choose key indicators in order to achieve precise source identification. Regardless of the emission inventory and models employed, Delhi consistently has significant underestimation of particulate matter concentrations, exacerbating its severe air pollution problems. The primary contributors to particulate matter in India are dust and emissions from transportation.

Atmospheric particulate matter and hypoxaemia in Korean children receiving general anaesthesia: A retrospective analysis.

The association between the concentration of atmospheric particulate matter on the day of surgery and the occurrence of intra-operative hypoxaemia in children receiving general anaesthesia is unclear. To investigate the association between the exposure to particulate matter on the day of surgery and the occurrence of intra-operative hypoxaemia, defined as a pulse oximetry oxygen saturation of less than 90% for more than 1 min, in children. Retrospective study. Single-centre. Children aged 18 years or younger who received general anaesthesia between January 2019 and October 2020. Information on daily levels of particulate matter with a diameter 10 μm or less and 2.5 μm or less measured within a neighbourhood corresponding to the area defined by the hospital's zip code was obtained from publicly available air-quality data. The primary outcome was intra-operative hypoxaemia, defined as a pulse oximetry oxygen saturation of less than 90% lasting for more than 1 min, manually verified by anaesthesiologists using vital sign registry data extracted at 2 s intervals. Of the patients finally analysed, 3.85% (489/13 175) experienced intra-operative hypoxaemia. Higher levels of particulate matter 10 μm or less in diameter (≥81 μg m -3 , 17/275, 6.2%) were associated with an increased occurrence of intra-operative hypoxaemia compared with lower particulate matter concentrations [<81 μg m -3 , 472/12 900, 3.7%; adjusted odds ratio, 1.71; 95% confidence interval (CI), 1.04 to 2.83; P = 0.035]. The level of particulate matter on the day of surgery pose a risk of intra-operative hypoxaemia in children receiving general anaesthesia. If the concentrations of particulate matter 10 μm or less in diameter on the day of surgery are high, children receiving general anaesthesia should be managed with increased caution.

Energy and environmental performance from field operation of commercial-scale SOFC systems

Solid Oxide Fuel Cells (SOFCs) are capable of generating electrical and thermal power with very high conversion efficiency and almost no pollutant emissions into the atmosphere. Despite extensive literature on SOFC-based energy system models and experimental testing at the cell and short-stack level, there is currently a lack of performance data for SOFC modules under actual field conditions. To fill this gap, the present work investigates the energy and environmental performance of six SOFC modules, ranging in size from 10 to 60 kW, over thousands of hours of operation. These systems, supplied by the three leading SOFC manufacturers in Europe, have been installed and operated in different non-residential buildings worldwide, as part of the European Comsos project. The aim of this study is to establish a comprehensive set of field operation data to characterise commercial-scale SOFC systems. Specifically, raw data are processed to derived electrical and thermal efficiency maps, degradation rates and pollutant emissions, including particulate matter (PM), nitrogen oxides (NOx) and carbon monoxide (CO). A comparison with competing technologies is also provided to better highlight the potential benefits of adopting SOFC-based cogeneration systems. Values in the range of 51–61% were found for the system-level electrical efficiency under rated conditions. The electrical efficiency also remained consistently high across a wide modulation range (between 50% and 100% of rated power), with peak values reaching 65%. In addition, promising results were obtained for the average percentage loss in electrical efficiency, with a minimum value of 0.7%/1000 h. Regarding the environmental analysis, NOx and CO emissions were analysed at both constant and variable power output, proving to be impressively low across the entire modulation range. The same applies to PM concentrations, which were below ambient level. Overall, SOFCs demonstrated to be one of the best cogeneration solutions for commercial-scale systems (tens to hundreds of kW in size), from both an energy and environmental perspective. However, further reductions in costs and dedicated financial schemes are necessary for a widespread market penetration.

Integrated Approach for the Assessment of Real Risk of Population Exposure in Industrial Areas

Research goal is to identify an integrated approach for assessing real risk exposure of population located in areas of extractive industries. We focused on environmental data evaluation (diffusion model), figures and contextual analysis of active health surveillance data of the population (questionnaire, chemistry panel, spirometry and activation of a biobank). Environmental exposure data crossed with the calculation of the AQI (Air Quality Index) did not highlight any critical issues. A cohort of 600 locals subjected to health surveillance was analysed by calculating risk perception; a questionnaire aimed at assessing risk perception was administered to the population sample.All data (environmental and clinical) were georeferenced and analysed using GIS (Geographic Information System) software; study of contaminant distribution was carried out using a Q-GIS software shows average exposure conditions well below regulatory limits, with minor exceptions relative to concentrations of finer particulate matter (PM 2.5) and with reference only to the major urban centers; analysis of risk perception evince “incorrect” perception, with little confidence in relation to the environmental monitoring of the Regional Agencies.

Geographic Variations in Urban‐Rural Particulate Matter (PM2.5) Concentrations in the United States, 2010–2019

AbstractFine particulate matter 2.5 (PM2.5) is a widely studied pollutant with substantial health impacts, yet little is known about the urban‐rural differences across the United States. Trends of PM2.5 in urban and rural census tracts between 2010 and 2019 were assessed alongside sociodemographic characteristics including race/ethnicity, poverty, and age. For 2010, we identified 13,474 rural tracts and 59,065 urban tracts. In 2019, 13,462 were rural and 59,055 urban. Urban tracts had significantly higher PM2.5 concentrations than rural tracts during this period. Levels of PM2.5 were lower in rural tracts compared to urban and fell more rapidly in rural than urban. Rural tract annual means for 2010 and 2019 were 8.51 [2.24] μg/m3 and 6.41 [1.29] μg/m3, respectively. Urban tract annual means for 2010 and 2019 were 9.56 [2.04] μg/m3 and 7.51 [1.40] μg/m3, respectively. Rural and urban majority Black communities had significantly higher PM2.5 pollution levels (10.19 [1.64] μg/m3 and 9.79 [1.10] μg/m3 respectively), in 2010. In 2019, they were: 7.75 [1.1] μg/m3 and 7.09 [0.78] μg/m3, respectively. Majority Hispanic communities had higher PM2.5 levels and were the highest urban concentration among all races/ethnicities (8.01 [1.73] μg/m3), however they were not the highest rural concentration among all races/ethnicities (6.22 [1.60] μg/m3) in 2019. Associations with higher levels of PM2.5 were found with communities in the poorest quartile and with higher proportions of residents age&lt;15 years old. These findings suggest greater protections for those disproportionately exposed to PM2.5 are needed, such as, increasing the availability of low‐cost air quality monitors.

Source apportionment of PM2.5 episodes in the Taichung metropolitan area, Taiwan

To analyze the physicochemical mechanisms affecting the variation in fine suspended particulate matter (PM2.5) concentrations in Taichung City, the largest city in central Taiwan (the second largest city in Taiwan), during a high-pollution event from November 3 to 6, 2021, we applied the sulfur tracking method (STM) and integrated source apportionment method (ISAM) of the WRF/CMAQ model to simulate the impacts of various emission sources. The sources of pollution in Taichung City are very similar, which shows that the impacts of point, line, and area sources should not be neglected in addition to the boundary conditions. SO42− is mainly generated from point emissions and the production of H2O2, Fe, Mn, and O3. NO3− is also mainly generated from point sources in Taichung City, with HNO3 being the main source at noon and ANO3 at other times of the day. NH4+ is mainly generated from area sources in Taichung City. OM is more complex, mainly originating from line sources in Taichung City and other sources, such as point/area emissions in Taichung City and other emissions from Changhua County. The most important mechanism is low-volatility/semivolatile oxidized combustion of OC at noon, followed by low-volatility/semivolatile POA, which is produced in the morning or evening. EC mainly originates from line sources in Taichung City and Changhua County. In other nearby counties, EC is dominated by local emission sources. In addition, when the concentration of PM2.5 is high, the Neutralization Ratio (NR) is high and PM2.5 is relatively neutral or slightly alkaline. On the contrary, when the concentration of PM2.5 is low, the NR is lower than 1 and the aerosol is acidic. Besides, this study used positive matrix factorization (PMF), which indicates that the PM2.5 at the UAPRS originated from eight kinds of pollution, namely, windblown dust, oil cracking, iron and steel industry, sea salt, transport, Cl− containing exhaust, biomass burning, fossil combustion containing abundant SO42− and the heavy oil refining and coal combustion industry. The direction of the source of pollution can be traced by a conditional bivariate probability function (CBPF). Overall, fossil fuel combustion, mainly involving sulfate, is the largest source of pollution, with the heavy oil refining and coal combustion industry contributing less, and the remaining factors contribute relatively evenly.

Evaluating background and local contributions and identifying traffic-related pollutant hotspots: insights from Google Air View mobile monitoring in Dublin, Ireland

Mobile monitoring provides high-resolution observation on temporal and spatial scales compared to traditional fixed-site measurement. This study demonstrates the use of high spatio-temporal resolution of air pollution data collected by Google Air View vehicles to identify hotspots and assess compliance with WHO Air Quality Guidelines (AQGs) in Dublin City. The mobile monitoring was conducted during weekdays, typically from 7:00 to 19:00, between 6 May 2021 and 6 May 2022. One-second data were aggregated to 377,113 8 s road segments, and 8 s rolling medians were aggregated to hourly and daily levels for further analysis. We assessed the temporal variability of fine particulate matter (PM2.5), nitrogen monoxide (NO), nitrogen dioxide (NO2), ozone (O3), carbon monoxide (CO), and carbon dioxide (CO2) concentrations at hyperlocal levels. The average daytime median concentrations of NO2 (28.4 ± 15.7 µg/m3) and PM2.5 (7.6 ± 4.7 µg/m3) exceeded the WHO twenty-four hours (24 h) Air Quality Guidelines in 49.4% and 9% of the 1-year sampling time, respectively. For the diurnal variation of measured pollutants, the morning (8:00) and early evening (18:00) showed higher concentrations for NO2 and PM2.5, mostly happening in the winter season, while the afternoon is the least polluted time except for O3. The low-percentile approach along with 1-h and daytime minima method allowed for decomposing pollutant time series into the background and local contributions. Background contributions for NO2 and PM2.5 changed along with the seasonal variation. Local contributions for PM2.5 changed slightly; however, NO2 showed significant diurnal and seasonal variability related to traffic emissions. Short-lived event enhancement (1 min to 1 h) accounts for 36.0–40.6% and 20.8–42.2% of the total concentration for NO2 and PM2.5. The highly polluted days account for 56.3% of total NO2, highlighting local traffic is the dominant contributor to short-term NO2 concentrations. The longer-lived events (> 8 h) enhancement accounts for 25% of the monitored concentrations. Additionally, conducting optimal hotspot analysis enables mapping the spatial distribution of “hot” spots for PM2.5 and NO2 on highly polluted days. Overall, this investigation suggests both background and local emissions contribute to PM2.5 and NO2 pollution in urban areas and emphasize the urgent need for mitigating NO2 from traffic pollution in Dublin.

Seasonal Indoor-to-Outdoor Ratio (I/O Ratio) of Fine Particulate Matter and Ozone Concentrations in Various Microenvironments in South Korea

Seasonal Indoor-to-Outdoor Ratio (I/O Ratio) of Fine Particulate Matter and Ozone Concentrations in Various Microenvironments in South Korea

Cover crops and deep‐soil C accumulation: What does research show after 10 years?

AbstractThe extent to which cover crops (CCs) accumulate soil organic carbon (SOC) in the entire soil profile is still unclear. We measured SOC, permanganate oxidizable C (POX‐C), and particulate organic matter (POM) concentrations down to 60‐cm soil depth in early [2–3 week before corn (Zea mays L.) planting]‐ and late‐terminated (at corn planting) winter rye (Secale cereale L.) CCs in rainfed and irrigated no‐till continuous corn systems in the U.S. Corn Belt after 10 years. CCs increased SOC stock and SOC, POX‐C, and POM concentrations but only in the irrigated system in the upper 5‐cm depth. Late‐terminated CC increased SOC concentration by 4.710 ± 3.501 g kg−1 and accumulated SOC at 0.207 ± 0.145 Mg C ha−1 year−1. It increased POX‐C and POM concentrations, on average, by 1.194 times. CCs likely increased SOC in the irrigated system by producing more biomass (2.247 ± 0.370 Mg ha−1) than in the rainfed system (0.949 ± 0.338 Mg ha−1). At least 2 Mg ha−1 of CC biomass may be needed to increase SOC. Because winter CCs often produce &lt;1 Mg ha−1 of biomass when typically planted late and terminated early, extending the CC growing window by terminating CCs at or after crop planting (planting green) may boost CC biomass and SOC accumulation, although high‐C soils or Mollisols, such as our study soils (&gt;22 g C kg−1), may limit SOC gains. We submit CCs would sequester more SOC in low‐C, eroded, and low‐fertility soils. Overall, winter rye CCs minimally alter soil C in the soil profile in no‐till continuous corn systems after 10 years.

Behavioral Responses to Wildfire Smoke: A Case Study in Western Montana.

Although climate change is increasing wildfire and smoke events globally, public health messaging and individual access to resources for protection are limited. Individual interventions can be highly effective at reducing wildfire smoke exposure. However, studies related to individual responses to wildfire smoke are limited and demonstrate mixed protective behaviors and risk perception. Our research helps fill this gap by assessing the self-reported behavior of 20 participants during wildfire season in Western Montana from 28 June through 1 November, 2022. We also measured continuous outdoor and indoor fine particulate matter (PM2.5) concentrations at participant residencies during this time period using PurpleAir sensors (PAII-SD, PurpleAir, Inc, USA) while participants took up to 16 self-reported online weekly activity surveys. Mixed-effect Poisson regression models were used to assess associations between exposure variables and participant reported behaviors. These results were compared with end-of-study interview findings. Wildfire smoke impacted days and increased concentrations of PM2.5 were associated with decreased outdoor exercise and opening of windows for ventilation. Interview themes were congruent with the regression analysis, with the additional finding of high portable air cleaner (PAC) use among participants. Additionally, these interviews gave context to both the tradeoffs participants face when making protective decisions and the importance of personal air quality data in increasing awareness about wildfire smoke risks. Future wildfire smoke studies can build off this research by providing personally relevant air quality data and PACs to participants and by improving public health messaging to address the compounding risks of wildfire smoke exposure and heat.

Assessment of clear-sky irradiance from 6S affected by local climatology of India

Accurate estimation of solar power generation is crucial for the effective planning and operation of solar energy sector. Solar potential can be estimated at a location from long-term historical irradiance data processed from atmospheric reanalysis datasets. The current study employs a clear-sky radiative transfer model (6S) to simulate the net surface irradiance at four distinct locations in India, comparing our model's output with mean monthly ground-based measurements of surface irradiance. Our findings reveal that the 6S model marginally underestimates solar irradiance, with potential deviations varying depending on the accuracy of input data. This research evaluates the influence of particulate matter concentration and relative humidity on the scattering and absorption of solar radiation. We also state the variability in surface irradiance across the country with the rainfall trends that enhance assessment accuracy. The study reports an annual deviation of 10–15 % in surface irradiance across the country, where rural settlements show lower deviations in simulations. The radiative transfer calculations mentioned in the study are simplistic yet beneficial for a priori evaluation of solar potential. Transmittance estimated from clear-sky models is further implemented in all-sky (with clouds), and thus, model accuracy is an important parameter. Additionally, we explore the trends in aerosol concentrations and the impact of local climatological factors on surface irradiance, providing insights critical for optimizing solar energy utilization.

Assessment of vertical transport of PM in a surface iron ore mine due to in-pit mining operations

Particulate matter (PM) is the most prevalent pollutant associated with surface mining operations, adversely affecting the health of mine workers. Using a combination of low-cost PM sensors and portable sampling devices, this research quantified the PM concentration and factors influencing its vertical transport inside a 100 m deep surface iron ore mine.Transport of ore through off-road trucks accounted for ∼ 70 % of the in-pit emissions. Also, differential settling and varying meteorological parameters along the vertical extent of the mine resulted in the escape of 17 % of PM2.5-10, 43 % of PM1-2.5, and 69 % of PM1to the mine’s surrounding atmosphere. Iron ore and carbon particles were identified as the major constituents of the airborne PM. The findings of this study demonstrate the application of low-cost sensors in monitoring PM concentration along the vertical extent of the mine, which can ultimately provide exposure estimates to the mine workers at different working locations.