High Concentrations Of Particulate Matter Research Articles

Assessing the Effects of Conservation Tillage and In-Situ Crop Residue Management on Crop Yield and Soil Properties in Rice–Wheat Cropping System

Rice–wheat cropping system (RWCS) is a dominant agricultural practice in the Indo-Gangetic plains, particularly in the North–Western states of India. The prevalent practice of open burning of rice residue, driven by the need for timely land preparation, poses severe environmental and health consequences, including nutrient loss, greenhouse gas emissions, high concentrations of particulate matter (PM), and disruption of the ecological cycle. This study focuses on implementing effective management practices in the RWCS through tillage-based crop establishment, residue retention, and incorporation methods. The objective is to improve crop yield and its attributes by enhancing soil health properties. A split-plot experimental design was practiced with four different treatments, zero-tillage with manual harvesting (ZT), Happy Seeder with combine harvester (HS), Happy Seeder with Mulcher and combine harvesting, and conventional tillage (CT). By evaluating soil nutrient content, including organic carbon (OC), N, P, and K, at a 0–10 cm depth, the study demonstrates the superiority of the mulcher with Happy Seeder (MHS), which significantly increased soil nutrient levels by 105, 59, 102, and 97%, respectively, compared to conventional tilled broadcasted wheat (CT). Furthermore, the MHS treatment exhibited the highest yield of 56.8 q ha−1, outperforming the yield of 43.6 q ha−1 recorded under conventional tilled broadcasted wheat. These findings underscore the critical role of surface residue retention with MHS in ensuring crop productivity and overall production sustainability of the RWCS in Haryana, India. Moreover, effective rice residue management holds long-term implications for agricultural resilience, farm economics, environmental conservation, and human health. It emphasizes the importance of adopting sustainable practices, prioritizing research efforts, and advocating for policies that ensure the prolonged sustainability and productivity of the RWCS while safeguarding environmental well-being.

Three-hourly PM2.5 and O3 concentrations prediction based on time series decomposition and LSTM model with attention mechanism

In recent years, air quality has attracted wide attention from all over the world, among which the high concentration of particulate matter with an aerodynamic less than 2.5 μm (PM2.5) and ozone (O3) has a great adverse impact on human health and daily life. Previous studies on two pollutant predictions are overly concerned with model improvement but hardly focus on influence variable screening, and pollutant's time series features extraction and identification. To better improve the prediction accuracy and enhance the application of the model in practice, in the present study, a novel model RF-CEEMDAN-Attention-LSTM was proposed, which has three processes: (1) random forest (RF) screened out highly correlated influence variables; (2) complete ensemble empirical mode decomposition with adaptive noise (CEEMADN) method was adopted to decompose the PM2.5 and O3 concentration time series into multiple sub-time sequences; (3) the double hidden layer LSTM model with attention and dropout mechanism captured nonlinear relationships and dynamic changes of time series features. Three-hourly PM2.5 and O3 concentration in Chengdu were used to validate the effectiveness of the developed RF-CEEMDAN-Attention-LSTM model by comparing five other parallel models. The final results showed that the model not only had a better fitting effect on both PM2.5 and O3 than other comparable models in the entire timeline, but the model also had the highest R2 (PM2.5:0.916, O3:0.525) values for these two air pollutants at high concentration values.

Healthcare utilization of lung cancer patients associated with exposure to fine particulate matter: A Korean cohort study.

Higher concentrations of particulate matter (PM) have been shown to cause deterioration of the symptoms of respiratory and cardiovascular disease in several regional studies. Here, we aimed to investigate the healthcare utilization of lung cancer patients associated with short-term exposure to PM at the national level in Korea. We extracted the data of 210 558 subjects over a period of 3 years (2015-2017), who were diagnosed with lung cancer before 2015 and benefited from the National Health Insurance Sharing Service. We performed the interpolation method using the geographic information system to calculate the estimated mean PM2.5 and PM10 concentrations by regions and classified three groups as high (upper 10%), intermediate (10%-90%), and low (bottom 10%) based on the mean PM mass concentrations of the month. The monthly average number of outpatient visits was significantly increased in high PM2.5 urban areas (46.296 vs. 50.646, p = 0.015). In high PM2.5 nationwide regions, the monthly average number of emergency admission was significantly increased (0.528 vs. 0.785, p = 0.001). The outpatient visits tended to change with PM2.5 concentration and correlated with PM10 /PM2.5 concentrations in urban and nationwide areas. In high PM2.5 urban regions, there was a significant increase in bronchodilator prescriptions (3.102 vs. 3.758, p = 0.008). Concerning high PM2.5 nationwide regions, there were significantly increased prescriptions of antibiotics, steroids, bronchodilators, antihistamines, and mucolytics. This study suggests that exposure to PM2.5 is significantly associated with hospital utilization and drug prescription in lung cancer patients.

Urban dust particles disrupt mitotic progression by dysregulating Aurora kinase B-related functions

Particulate matter (PM), a major component of outdoor air pollution, damages DNA and increases the risk of cancer. Although the harmful effects of PM at the genomic level are known, the detailed mechanism by which PM affects chromosomal stability remains unclear. In this study, we investigated the novel effects of PM on mitotic progression and identified the underlying mechanisms. Gene set enrichment analysis of lung cancer patients residing in countries with high PM concentrations revealed the downregulation of genes associated with mitosis and mitotic structures. We also showed that exposure of lung cancer cells in vitro to urban dust particles (UDPs) inhibits cell proliferation through a prolonged M phase. The mitotic spindles in UDP-treated cells were hyperstabilized, and the number of centrioles increased. The rate of ingression of the cleavage furrow and actin clearance from the polar cortex was reduced significantly. The defects in mitotic progression were attributed to inactivation of Aurora B at kinetochore during early mitosis, and spindle midzone and midbody during late mitosis. While previous studies demonstrated possible links between PM and mitosis, they did not specifically identify the dysregulation of spatiotemporal dynamics of mitotic proteins and structures (e.g., microtubules, centrosomes, cleavage furrow, and equatorial and polar cortex), which results in the accumulation of chromosomal instability, ultimately contributing to carcinogenicity. The data highlight the novel scientific problem of PM-induced mitotic disruption. Additionally, we introduce a practical visual method for assessing the genotoxic outcomes of airborne pollutants, which has implications for future environmental and public health research.

FORECASTING OF AIR POLLUTION WITH TIME SERIES AND MULTIPLE REGRESSION MODELS IN SOFIA, BULGARIA

Air pollution is one of the serious environmental problems. The high concentrations of particulate matter can have a serious impact over human health and ecosystems, especially in highly urbanized areas. In this regard, the present study employs a combined ARIMA-Multiple Linear Regression modelling approach for forecasting particulate matter content. The capital city of Bulgaria is used as case study. A regression analysis techniques are used to study the relationship between particulate matter concentration and basic meteorological variables – air temperature, solar radiation, wind speed, wind direction, atmospheric pressure. The adequacy of the models has been proven by examining the behavior of the residues. The synthesized time series model can be used for forecasting, monitoring and controlling the air quality conditions. All analyzes and calculations were performed with statistical software STATGRAPHICS.

Analyzing indoor air pollutants in naturally ventilated athletic facilities. A case of study

Better indoor air quality (IAQ) lowers the exposure to air pollutants that can lead to decreased lung function, and exacerbation of common recurring respiratory conditions, such as asthma. Due to the higher respiratory rate, these adverse effects are particularly dangerous for athletes during exercise. Thus, investigating, and mitigating exposure to air pollutants during exercise is necessary in athletic centers. Among such facilities, cross-training gymnasiums are becoming increasingly popular and are commonly not equipped with HVAC systems, relying solely on natural ventilation to create a comfortable and healthy indoor environment. This study investigated the impact of 16 scenarios combining natural ventilation, fans, and air cleaner, on the IAQ of an athletic facility in San Antonio, TX, USA. For this purpose, occupancy, Carbon Dioxide (CO2), Carbon Monoxide (CO), Total Volatile Organic Compounds (TVOC), Particulate Matter (PM), as well as indoor and outdoor air temperature and relative humidity levels were monitored for 3 months in 5-min intervals to identify health threatening patterns. Results showed that some ventilation scenarios presented high concentrations of CO2, TVOC and PM exceeding the recommended limit values, while CO did not present concerning levels regardless of the ventilation strategy. Temperature levels indoors were consistently higher than outdoors, while relative humidity levels were lower inside. Remarkably, air filtration did not show a significant impact on IAQ in any of the analyzed scenarios. These results prove that it is essential to optimize the natural ventilation and occupancy in order to reduce the exposure to air pollutants in naturally ventilated fitness centers.

Association between spill-related exposure to fine particulate matter and peripheral motor and sensory nerve function among oil spill response and cleanup workers following the Deepwater Horizon oil spill.

Burning/flaring of oil/gas during the Deepwater Horizon oil spill response and cleanup (OSRC) generated high concentrations of fine particulate matter (PM2.5). Personnel working on the water during these activities may have inhaled combustion products. Neurologic effects of PM2.5 have been reported previously but few studies have examined lasting effects following disaster exposures. The association of brief, high exposures and adverse effects on sensory and motor nerve function in the years following exposure have not been examined for OSRC workers. We assessed the relationship between exposure to burning/flaring-related PM2.5 and measures of sensory and motor nerve function among OSRC workers. PM2.5 concentrations were estimated from Gaussian plume dispersion models and linked to self-reported work histories. Quantitative measures of sensory and motor nerve function were obtained 4-6 years after the disaster during a clinical exam restricted to those living close to two clinics in Mobile, AL or New Orleans, LA (n = 3401). We obtained covariate data from a baseline enrollment survey and a home visit, both in 2011-2013. The analytic sample included 1186 participants. We did not find strong evidence of associations between exposure to PM2.5 and sensory or motor nerve function, although there was a suggestion of impairment based on single leg stance among individuals with high exposure to PM2.5. Results were generally consistent whether we examined average or cumulative maximum exposures or removed individuals with the highest crude oil exposures to account for co-pollutant confounding. There was no evidence of exposure-response trends. Remediating environmental disasters is essential for long-term human and environmental health. During the Deepwater Horizon oil spill disaster, burning and flaring of oil and gas were used to remove these pollutants from the environment, but led to potentially high fine particulate matter exposures for spill response workers working on the water. We investigate the potential adverse effects of these exposures on peripheral nerve function; understanding the potential health harm of remediation tactics is necessary to inform future clean up approaches and protect human health.

Developing a Decision-making Tool for Agricultural Surface Water Decontamination Using Ultraviolet-C Light

Ultraviolet-C (UV-C) light-assisted water treatment systems are an increasingly investigated alternative to chemical sanitizers for agricultural surface water decontamination. However, the relatively high concentration of particulate matter in surface water is a major challenge to expanding its application in the production of fresh produce. The objective of this project was to test the efficacy of two commercial UV-C devices to reduce the microbial risk of agricultural water in order to develop a web application to assist growers in decision-making related to the on-farm implementation of UV-C technologies for agricultural water treatment. An on-farm study using three agricultural water sources was performed to determine the microbial reduction efficacy of a low power, low flow (LP/LF; 1–9 gallons per minute (GPM), 1.34-gallon capacity) and a high powered, high flow (HP/HF; 1–110 GPM, 4.75-gallon capacity) device at flow rates of 6, 7, and 9 GPM. A threshold of 30% UVT for the HP/HF device was observed, wherein lower water transmissibility significantly impacted microbial inactivation. Although less effective at lower %UVT, the LP/LF device costs less to install, maintain, and operate. The observations were used to design an online tool for growers to calculate the predicted reduction of generic Escherichia coli using either device based on the %UVT of their water source. However, because this study utilized an exploratory and proof-of-concept approach, the experimental flow rates were limited to reflect the capacities of the smaller unit (9 GPM) for direct comparison to the larger unit. Thus, the preliminary model and tool are largely limited to the experimental conditions. Yet, these results of this study demonstrate the utility of UV-C light in reducing the microbial risk of agricultural water, and future studies using different UV-C devices and higher flow rates will expand the use of the decision-making tool.

Secondhand electronic cigarette aerosol in vehicles impacts indoor air quality

BackgroundElectronic cigarette (ECIG) use in vehicles represents a public health concern due to the potential for exposure to high concentrations of particulate matter (PM) and other toxicants. This study examined the impact of ECIG use on air quality in vehicles. MethodsPeople who reported current ECIG use (n=60; mean age=20.5, SD=2.3) completed a brief survey and a 30-min ECIG use session in their own vehicle. Using a protocol similar to clinical laboratory studies involving tobacco use, participants took 10 directed puffs (i.e., a directed bout with one puff every 30s for 5min) followed by a 25-min ad libitum period in which participants took as many puffs as desired. PM 2.5µm in diameter or smaller (PM2.5) were measured using aerosol monitors set up to sample air from the breathing zone of the passenger seat and total puffs were recorded. The association between peak PM2.5 concentration and puff count was examined. ResultsParticipants took a median 18 total puffs during the sessions. Median PM2.5 concentrations increased from 4.78µg/m3 at baseline to 107.40µg/m3 after the directed bout. Median peak PM2.5 concentration was 464.48µg/m3 and ranged from 9.56µg/m3 to 143,503.91µg/m3 (IQR=132.72–1604.68). After removing two extreme outliers for puff count and PM2.5 concentrations, puff count was significantly correlated with peak PM2.5 concentration during the ad libitum bout (r=0.32, p=0.015). ConclusionsECIG use in vehicles impacts air quality negatively and may pose health risks to those present in vehicles when ECIG use is occurring.

Ventilation Strategies for Highly Occupied Public Environments: A Review

In urban public transportation and highly diversified air environments, air pollutant exposure is becoming an increasing concern in terms of public health and personal safety. Herein, the scientific literature on air quality and virus transmission in densely crowded environments is reviewed to determine effective control methods. The research results are classified on the basis of different crowded environments. Much research has been conducted on pollutants in subways and buses. High particulate matter concentrations in public transportation are still a serious problem, but few studies on the spread of viruses exist. With existing types of ventilation systems, increasing local exhaust may be an efficient way to remove pollutants. Air quality sensors should be distributed in densely crowded spaces to achieve real-time display of pollutant concentration data. When pollution levels exceed the safe values, scientifically designed ventilation and filtration schemes should be implemented to reduce the pollution levels. Occupant activities are among the important factors that make pollutant transmission more complex. The analysis results herein contribute to the assessment of indoor pollutant concentrations and the protection of occupants from cross-infection.

Time-Frequency Domain Variation Analysis and LSTM Forecasting of Regional Visibility in the China Region Based on GSOD Station Data

Atmospheric visibility is an important indicator that reflects the transparency of the atmosphere and characterizes the air quality, so it is of great significance to study the long-term change in visibility. This paper is based on the global surface summary of day data (GSOD) site dataset and other relevant data, using the Mann–Kendall (MK) mutation point test, wavelet transform, and seasonal autoregressive integrated moving average (SARIMA) model forecasting. The time-frequency domain variation characteristics and related influencing factors of regional visibility in China were studied in detail, and the visibility was predicted; the results of the study showed the following: (1) the overall interannual variation of regional visibility in China has a decreasing trend, and the four-season variation has a decreasing trend, except for the rising trend in summer, with abrupt change points in both the overall interannual variation and the four-season variation. (2) There are main cycles of visibility in the Chinese region with time scales of 180 months and 18 months. Under the time scale of 180 months for the main cycle, the variation period of visibility is about 123 months, experiencing two high to low variations; under the time scale of 18 months for the main cycle, the variation period of visibility is 12 months, experiencing 21 high to low variations. (3) The development of the economy indirectly affects changes in visibility. Cities with high economies are densely populated, with concentrations of various particulate emissions and high concentrations of particulate matter, which can directly reduce visibility. (4) Two prediction models, SARIMA and long and the short-term memory (LSTM) neural network, were used to predict the visibility in China, both of which achieved good evaluation indexes, and the visibility in China may show an increasing trend in the future.

A fjord with a land-terminating glacier: Meltwater, bio-optics, particulate matter, nutrients, phytoplankton species, and primary production in west Greenland

Land-terminating glaciers and submarine melting of marine-terminating glaciers are significant features in Arctic regions and are foreseen to become more frequent as marine-terminating glaciers ultimately develop into a land-terminated state. A transition driven by the continuous rise in Arctic air temperatures, and emphasizes the importance of studies of land-terminating glaciers their bio-optical properties and biogeochemistry. Kangerlussuaq in west Greenland with a land-terminating glaciers and was selected for this study. During a research cruise we measured spectral and PAR attenuation, particulate matter concentrations, salinity, nutrient concentrations, Chla, and phytoplankton species composition, along a transect from river outlet to open marine waters. Results showed that surface waters in Kangerlussuaq were strongly influenced by meltwater with low salinities, high particulate matter concentrations, high PAR and spectral light attenuation coefficients, and low nutrient concentrations. Spectral composition was also affected by the particulate matter. PAR photic depths varied between 4 and 9 m dependent on particulate matter concentrations. There was a decrease with distance from outlet in silicate concentrations, and opposite for phosphate, which increased significantly from river outlet to the marine. Phytoplankton species number (42) and diversity were high at the marine station but low (3) in turbid waters dominated by the diatom Skeletonema costatum in high numbers. A meltwater plume covered about 50 % of the Kangerlussuaq at average discharges in early August. Primary production was quantified with a simple model based on light attenuation coefficients, and showed a near exponential decrease in production with increase in attenuation.

Spatiotemporal exposure of motorcyclists to particulate matter in a densely populated urban area: A case study of Varanasi, India

Researchers have studied motorcyclists' exposure to Particulate Matter (PM) during rush and non-rush hours. However, the combined effect of season and hour of the day on PM concentration has not been studied. PM concentration was measured near the typical breathing zone of motorcyclists who traveled along four designated routes in a densely populated city (Varanasi, India). Data were collected from January to June 2022 during various hours of the day (from 07:00 to 17:00 h). PM2.5 and PM10 concentration during winter was 2.36 and 1.69 times in summer, respectively. In contrast, PM2.5 and PM10 concentration during spring were 1.35 and 1.12 times during summer, respectively. PM2.5 correlated much more with relative humidity and atmospheric temperature than PM10. Higher PM concentration was recorded in rush hour (09:00–10:00) during spring and summer but in non-rush hours (12:00–13:00) during winter. The opposite trend in the winter was caused by more extended dispersion and dilution time of PM particles. Also, a higher proportion of PM2.5 was observed on routes with longer rush hours caused due to road encroachment by street vendors and pedestrians.

Contribution of local and surrounding anthropogenic emissions to a particulate matter pollution episode in Zhengzhou, Henan, China

In this study, we simulated the spatial and temporal processes of a particulate matter (PM) pollution episode from December 10–29, 2019, in Zhengzhou, the provincial capital of Henan, China, which has a large population and severe PM pollution. As winter is the high incidence period of particulate pollution, winter statistical data were selected from the pollutant observation stations in the study area. During this period, the highest concentrations of PM2.5 (atmospheric PM with a diameter of less than 2.5 µm) and PM10 (atmospheric PM with a diameter of less than 10 µm) peaked at 283 μg m-3 and 316 μg m-3, respectively. The contribution rates of local and surrounding regional emissions within Henan (emissions from the regions to the south, northwest, and northeast of Zhengzhou) to PM concentrations in Zhengzhou were quantitatively analyzed based on the regional Weather Research and Forecasting model coupled with Chemistry (WRF/Chem). Model evaluation showed that the WRF/Chem can accurately simulate the spatial and temporal variations in the PM concentrations in Zhengzhou. We found that the anthropogenic emissions south of Zhengzhou were the main causes of high PM concentrations during the studied episode, with contribution rates of 14.39% and 16.34% to PM2.5 and PM10, respectively. The contributions of anthropogenic emissions from Zhengzhou to the PM2.5 and PM10 concentrations in Zhengzhou were 7.94% and 7.29%, respectively. The contributions of anthropogenic emissions from the area northeast of Zhengzhou to the PM2.5 and PM10 concentrations in Zhengzhou were 7.42% and 7.18%, respectively. These two areas had similar contributions to PM pollution in Zhengzhou. The area northeast of Zhengzhou had the lowest contributions to the PM2.5 and PM10 concentrations in Zhengzhou (5.96% and 5.40%, respectively).

Role of urban boundary layer dynamics and ventilation efficiency in a severe air pollution episode in Tehran, Iran

Tehran faces a significant health challenge due to severe air pollution episodes during wintertime, which are associated with high concentrations of fine particulate matter with a diameter less than 2.5 µm (PM2.5). In this study, we investigated meteorology conditions of one of the severe air pollution episodes, occurred from 27th December 2020 to 15th January 2021, using the Weather Research and Forecasting (WRF) model. To gain insights into this episode, we also modeled a clean episode for comparison. Model validation of land surface temperature using remote sensing showed acceptable performance as well as ground observations for other parameters. We then calculated the ventilation coefficient (VC) from the WRF outputs and analyzed the results statistically. Results indicate the severe reduction in both VC and planetary boundary layer height (PBLH) during the polluted episode. We further linked the decrease in PBLH and VC of the polluted episode to a high-pressure system above 1020 hPa. In contrast, the results for the clean episode indicate that the low-pressure system as low as 1010 hPa led to higher PBLH and VC than during the polluted episode. This low-pressure system favors the reduction of PM2.5 levels to lower than 21 μgm−3.

Combined effect of surface PM2.5 assimilation and aerosol-radiation interaction on winter severe haze prediction in central and eastern China

In this study, the effects of aerosol-radiation interaction (ARI) and data assimilation (DA) during a haze episode in December 2016 are evaluated by four sets of parallel experiments using the atmospheric chemical model GRAPES_Meso5.1/CUACE. The results show that although the BASE experiment without ARI and DA generally captures the variations of particulate matter (PM) and visibility (VIS), it dramatically underestimates the high PM concentrations and overestimates the low VIS on severe haze days. Moreover, the ARI effect is not significant when the aerosol concentration is relatively low (PM2.5 <150 μgm−3). Assimilation of surface PM2.5 corrects the model chemical initial conditions (ICs) and increases the aerosol concentration in severe haze areas. Focusing on the severe pollution periods, the combined effect of ARI and DA significantly improves forecast accuracy and prolongs this improvement, which reduces the average negative biases of PM2.5 and PM10 by 33% and 35%, and increases the average correlation coefficients by 14% and 12%. Moreover, this combined effect also changes the vertical distribution of the atmosphere, especially at a low level, leading to a 2.6 K decrease in potential temperature (PT) and a 7.6% increase in relative humidity (RH) below 300 m. Due to the contributions of PM and RH, the low VIS prediction is significantly improved, with the root mean square error (RMSE) reduced by 30%. The study results show the combined effect of ARI and DA on aerosols and meteorology and suggest the importance of considering ARI and DA simultaneously in the atmospheric chemical model.

Association between short-term air pollution exposure and traumatic intracranial hemorrhage: pilot evidence from Taiwan.

The detrimental effects of air pollution on the brain are well established. However, few studies have examined the effect of air pollution on traumatic brain injury (TBI). This pilot study evaluated the association between short-term air pollution exposure and traumatic intracranial hemorrhage (TIH). Hospital data of patients with TBI following road traffic accidents were retrospectively collected from the electronic medical records at five trauma centers in Taiwan between 1 January and 31 December 2017. TIH was employed as an outcome measure. All road accident locations were geocoded, and air quality data were collected from the nearest monitoring stations. Air pollutants were entered into five multivariable models. A sensitivity analysis was performed on patients who are vulnerable to suffering TBI after road accidents, including motorcyclists, bicyclists, and pedestrians. Among 730 patients with TBI, 327 had TIH. The ages of ≥65 [odds ratio (OR), 3.24; 95% confidence interval (CI), 1.85-5.70], 45-64 (OR, 2.61; 95% CI, 1.64-4.15), and 25-44 (OR, 1.79; 95% CI, 1.13-2.84) years were identified as significant risk factors in the multivariable analysis. In the best-fit multivariable model, exposure to higher concentrations of particulate matter ≤ 2.5 μm in aerodynamic diameter (PM2.5) was associated with an elevated TIH risk (OR, 1.50; 95% CI, 1.17-1.94). The concentration of nitrogen oxides (NOX) did not increase the risk of TIH (OR, 0.45; 95% CI, 0.32-0.61). After categorizing the air pollution concentration according to quartile, the trend tests in the multivariate model showed that the concentrations of PM2.5 and NOX were significant (p = 0.017 and p < 0.001, respectively). There was a negative borderline significant association between temperature and TIH risk (OR, 0.75; 95% CI, 0.56-1.00, p = 0.05). Notably, the single-vehicle crash was a significant risk factor (OR, 2.11; 95% CI, 1.30-3.42) for TIH. High PM2.5 concentrations and low temperatures are risk factors for TIH in patients with TBI. High NOX concentrations are associated with a lower TIH risk.

Impact of Particulate Matter (PM10 and PM2.5) from a Thermoelectric Power Plant on Morpho-Functional Traits of Rhizophora mangle L. Leaves

A conventional thermoelectric plant (TP) in the sandy bar of the Tampamachoco Lagoon (Gulf of Mexico slope) emits particulate matter (PM) transporting trace metals that affect a mangrove forest. Wind transports the emission plume from north to south in the northerly wind season (NWS); the dry season (DS) showed calm periods. We analyzed whether PM2.5 and PM10 emissions from the TP and their trace metals impact Rhizophora mangle leaves. The experimental design included three sampling sites along the main lagoon axis (north to south) during the NWS and DS. Mangrove leaves were collected; PM was obtained with a cascade impactor and trace elements were analyzed by atomic absorption spectrophotometry. Leaves were measured and tested for metal and chlorophyll content, and for metal detection with SEM-EDX. Calm periods in the DS promote high atmospheric PM concentrations. Wet deposition in the NWS caused the highest trace metal deposition on mangrove leaves. A north-to-south gradient was identified on the mangrove forest, being the south site of the lagoon where lower chlorophyll and leaf area, higher stomatal width and density, and higher Cd concentrations were recorded. The morpho-physiological modifications observed on mangrove leaves affect functions such as photosynthesis and gas exchange.

미세먼지의 야외 여가활동 수요에 대한 효과

As the damage of particulate matter (PM) becomes known to the public recently, both mitigation and adaptation to highly concentrated PM have been emphasized. While it has been found that the tendency to avoid PM can also affect the decision-making of outdoor activities, some studies show a positive correlation between PM concentration and visitations. In this extension, this study examines how PM concentration affects the visiting behavior of national parks. For this, we used the actual daily visitation data (from January 1, 2014 to June 30, 2020) to 20 national parks from Korea National Park Service by adopting the fixed effect panel model. The results showed that a positive relationship between the number of visitors and PM concentration but it is insignificant. The results also showed that people are more sensitive to whether or not the high PM concentration than to PM concentration value itself and they reduce visitations as PM concentration level becomes ‘bad’ or worse. In addition, the correlation between PM concentration and visitations appears in a different pattern in winter than in other seasons. These results implies that a simple analysis on the relationship between PM concentration and outdoor activity can lead to misunderstanding and that there is something else people consider more than PM concentration level.

Air quality impacts on rooftop photovoltaic energy production during the 2019–2020 Australian bushfires season

The ”Black Summer” 2019–2020 bushfires covered large areas of eastern Australia, causing substantial health impacts, animal deaths and damage to infrastructure. The smoke-related aerosols produced from these fires can also impact solar energy production by attenuating useable radiation. This study assesses the impacts of high particulate matter (PM) concentrations in photovoltaic (PV) energy production in New South Wales (NSW), from November 2019 to January 2020, during the bushfire season. We use in-situ measurements of commercial rooftop PV systems, pollution data from NSW Air Quality Monitoring Network and the Schools Weather and Air Quality, and satellite information from Himawari-8. We focus the study on clear days to eliminate the effects of clouds and concentrate on the impact of PM alone. We compare the energy generated by rooftop PV systems during clean/polluted conditions with a statistical conditional analysis approach. Results show that most locations exhibit similar behaviour, with PV generation reductions in polluted environments compared to clean conditions. The air quality impacts are stronger in locations near bushfire burning areas. For instance, in Katoomba, mean reductions up to 20% in the generated PV energy are found during high PM episodes. High-speed westerly winds transported the smoke several hundreds of kilometres, influencing the air quality and PV energy generation in most stations across Sydney. On a particular day of high bushfire activity (10 December 2019), we use satellite information to show how smoke caused increases in aerosol levels, increased PM concentrations, attenuated radiation and produced up to 65% reductions in hourly PV energy.