Measurements Of PM2 Research Articles

Particulate Matter (PM10) Sources in Bizerte, Tunisia Using Logistic Regression Model

Short-term exposure to particulate matter (PM10), the total mass of PM with a diameter of 10 micrometers or less, has been linked to increased morbidity and mortality. Most of the dust particles released to the atmosphere worldwide is emitted by Saharan Desert in North Africa. This paper evaluates the effect of dust particles from African regions on PM10 concentrations in Bizerte, Tunisia using a logistic regression statistical methodology. The 2004 and 2005 PM10 measurements were obtained by the Tunisian National Agency for Environmental Protection, ANPE, pollution monitoring station and for the same period, 6-day back trajectories were generated using the NOAA-HYSPLIT. The study found that the DLV exceeded the 50-μg/m³ limit 293 times in 2004 and 257 times in 2005. Significant associations have been found between far air sources and the measured concentrations for both 2004 (OR=1.024, 95% CI = 1.016-1.032) and 2005 (OR=1.013, 95% CI = 1.003-1.022). The model performance has significantly improved when shorter back trajectories (closer source regions) were considered. The feasibility of using a logistic regression statistical methodology to evaluate the effect of air masses from African regions on PM10 concentrations in Bizerte, Tunisia has been demonstrated.

Exposure of children to fine particles (PM2.5 and PM10) in schools in the health districts of Yopougon, Abidjan

Background: In Africa, the school environment is becoming a growing concern, as concentrations of fine particles inside classrooms are very high. We decided to estimate the level of exposure to PM2.5 and PM10 of schoolchildren in the health districts of Yopougon in Abidjan. Methods: This was an analytical cross-sectional study of pupils aged 8 to 14 years in the health districts of Yopougon. Our study was conducted from 24 November 2020 to 18 January 2021. The pupils were selected by two-stage random sampling. A real-time fine-particle measurement instrument, the DYLOS 1700, and the ISAAC questionnaire were used to collect the parameters studied. Results: We surveyed 881 pupils from 08 schools. The sex ratio (M/F) of the pupils was 0.9 and the mean age was 12 years. Measurements of PM2.5 and PM10 levels in the classrooms were 30 times higher than WHO standards and ranged from 200 to 1000 µg/m3 and 1000 to 3000 µg/m3 respectively. There was a significant link between the presence of pollution sites near schools and the increase in PM2.5 and PM10 levels in classrooms. Clinical manifestations suggestive of asthma in pupils were significantly associated with high levels of PM2.5 and PM10. Conclusions: Pupils in Yopougon’s schools are exposed to high level of fine particle pollution that exceed WHO standards. Respecting and applying pollution reduction measures will help to create a school environment that is favourable to the respiratory health of pupils.

Measurement of PM2.5 Concentrations and Comparison of Affecting Factors in Residential Houses in Summer and Autumn

Measurement of PM_2.5 Concentrations and Comparison of Affecting Factors in Residential Houses in Summer and Autumn

Desert dust episodes during pregnancy are associated with increased preterm delivery in French Guiana.

Preterm deliveries are a major multifactorial public health problem in French Guiana. Desert dust episodes have been associated with preterm delivery in Guadeloupe, a territory with similarities to French Guiana. We thus tried to replicate this finding in the context of French Guiana. A retrospective ecological cohort study combined daily PM10 concentration measurements during pregnancy and term at delivery extracted from French Guiana's computerized pregnancy delivery registry. Daily PM10 concentrations during the course of pregnancy were analyzed as mean concentrations and as the proportion of intense dust episodes (≥55 μg PM10/m3). These exposure variables were studied in relation to the outcome of preterm delivery. Overall, 3,321 pregnant women with complete daily PM10 measurements were included, of whom 374 (11.26%) delivered prematurely. Among preterm deliveries, 168 (44.9%) were spontaneous deliveries and 206 (55.1%) were induced. Rank-sum tests showed that, for spontaneous and induced spontaneous deliveries, both mean PM10 concentrations and proportions of intense desert dust episodes were significantly greater among preterm births than among term births. Although the proportion of intense desert dust episodes during pregnancy was significantly associated with spontaneous preterm deliveries, the relation was U-shaped, with an adjusted odds ratio (AOR) = 2 (95%CI = 1.2-3.1) for lowest values relative to median values and AOR = 5.4 (95%CI = 3.2-8.9) for the highest values relative to median values. Similarly, the proportion of intense desert dust episodes during pregnancy was also significantly associated with induced preterm deliveries in a U-shaped manner (AOR = 2.7 (95%CI = 1.6-4.5) for the lowest relative to median values and AOR = 6.8 (95%CI = 3.9-11.9) for the highest relative to median values). Although in our study the relation between PM10 concentrations appeared non-linear, the highest mean concentrations and intense desert dust episodes were indeed associated with both spontaneous and induced preterm delivery.

The Assessment of PM2.5 and PM10 Immission in Atmospheric Air in a Climate Chamber during Tests of an Electric Car on a Chassis Dynamometer

Electric cars, like internal combustion vehicles, emit particulate pollution from non-exhaust systems, i.e., tires and brakes, which is included in the Euro 7 emission standard planned for implementation. Tests conducted on chassis dynamometers are accompanied by particulate emissions from non-exhaust systems, which are introduced into the ambient air on the test bench. Particulate emissions tests from non-engine systems on chassis dynamometers are mainly aimed at measuring the mass or number of particulates from tires and brakes. In contrast, little attention is paid to the immission of particulate matter from tires and brakes on the dynamometer during tests, which in the case of electric cars include, for example, measurements of energy consumption or range. Therefore, in order to draw attention to the problem of these emissions, the authors carried out measurements of PM2.5 and PM10 immissions into the air in the climatic chamber during tests of an electric car on a chassis dynamometer. The car tests were carried out in accordance with the WLTC (Worldwide harmonized Light duty Test Cycle) and at constant speed. Based on the test results, a model was proposed for the immission of particulate matter in laboratory air from tire and brake abrasion, taking traffic parameters into account. The results and the developed model show that air quality, in terms of particulate content, deteriorates significantly during testing.

The contribution of residential wood combustion to the PM2.5 concentrations in the Helsinki metropolitan area

Abstract. This article has investigated the contribution of residential wood combustion (RWC) to the fine particulate matter (PM2.5) concentrations in the Helsinki metropolitan area (HMA) for 6 years, from 2009 to 2014. We have used the PM2.5 concentrations measured at eight air quality measurement stations. The dispersion of emissions on an urban scale was evaluated with multiple-source Gaussian dispersion models, UDM-FMI (urban dispersion model of the Finnish Meteorological Institute) and CAR-FMI (Contaminants in the Air from a Road model of the Finnish Meteorological Institute), and on a regional scale using the chemical transport model SILAM (System for Integrated modeLling of Atmospheric coMposition). The overall agreement of the predicted concentrations with measurements of PM2.5 was good or fairly good for all stations and years; e.g. at the permanent residential station the daily average values of the index of agreement ranged from 0.69 to 0.81, and the fractional bias values ranged from −0.08 to 0.11, for the considered 6 years. Both the measured and predicted daily averaged concentrations showed increasing trends towards the lower-temperature values. The highest predicted annual averaged concentrations in the region occurred in the vicinity of major roads and streets and in the suburban residential areas to the northwest, north, and northeast of the city centre. The average concentrations of PM2.5 attributed to RWC in winter were up to 10- or 15-fold, compared to the corresponding concentrations in summer. During the considered 6-yearly period, the spatially highest predicted fractions of RWC of the annual PM2.5 concentrations ranged from 12 % to 14 %. In winter, the corresponding contributions ranged from 16 % to 21 %. The RWC contribution was higher than the corresponding urban vehicular traffic contribution at all the residential stations during all years. The study has highlighted new research needs for the future, in particular (i) the modelling of the RWC emissions that would be explicitly based on the actual ambient temperatures and (ii) the modelling of the impacts of the most important holiday periods on the emissions from RWC.

Equivalence of low-cost PM10 concentration measuring devices with a reference method using various correction functions

The aim of the study was to build a corrective model that can be used in the analysed devices and to assess the impact of such a model on the values of the measured concentrations. The novelty of this study is the test of equivalence with the equivalent reference method for hourly data. The study used hourly data of PM10 concentrations measured in a chosen city in Poland. Data was collected from two PM10 sensors and a reference device placed in close proximity. In addition, air temperature, humidity and wind speed were also measured. Among the tested models, a linear model was selected that used primary measurements of PM10, temperature, air velocity, and humidity as the most accurate approximation of the actual PM10 concentration level. The results of the analysis showed that it is possible to build mathematical models that effectively convert PM10 concentration data from tested low-cost electronic measuring devices to concentrations obtained by the reference method.

Estimation of hourly one square kilometer fine particulate matter concentration over Thailand using aerosol optical depth

In the recent years, concentration of fine particulate matter that are 2.5 microns or less in diameter (PM2.5) in Thailand has consistently exceeded the national ambient air quality standard. Currently, the measurement of PM2.5 concentration relies on air quality monitoring stations operated by the Pollution Control Department of Thailand (PCD). However, these stations are insufficient, particularly in rural areas, where agricultural open burning are major sources of pollution after harvesting period. This study aims to enhance the monitoring of PM2.5 concentration by leveraging cost-effective technologies. We propose the integration of satellite data, specifically Aerosol Optical Depth (AOD) from Multi-Angle Atmospheric Correction (MAIAC) product and Himawari-8 satellites, with the Weather Research and Forecasting Model (WRF) data, to provide supplementary data to the ground-based monitoring. Hourly 5 × 5 km2 AOD data from Himawari-8 were downscaled to a high-resolution of 1 × 1 km2, leveraging the AOD distribution pattern of the concurrent MAIAC product using eXtreme Gradient Boosting (XGBoost) model. Notably, during Thailand’s rainy season (May to August), the study observed a relative reduction in the training model’s R-square value. This phenomenon is attributed to temporal discrepancies between Himawari-8 and the MAIAC products during this period. The predictive models of PM2.5 concentrations with the identification of pertinent variables through Pearson’s correlation analysis and recursive feature elimination, driven by the robust XGBoost model. Subsequently, the downscaled AOD, wind speed, temperature, and pressure were identified as predictors for the estimation of hourly PM2.5 concentration. This comprehensive approach enabled the projection of PM2.5 levels across Thailand, encompassing over 600,000 grids at 1 × 1 km2 resolution. The developed models, thus, offer a valuable tool for robust and high-resolution PM2.5 concentration estimation, presenting significant implications for air quality monitoring and management in Thailand.

Health risk analysis of heavy metal exposure bonded in PM2.5 at industrial area in Bandung Regency

Heavy metal contents in PM2.5 particulate dust poses potential risk to the health of human beings. This study aims to measure PM2.5 dust concentrations and characterize heavy metals bound in PM2.5 to estimate health risks in both children and adult groups. PM2.5 dust was measured in Bandung Regency in industrial land uses, located in the Dayeuhkolot sub-district. Measurement of PM2.5 concentrations using a Low Volume Air Sampler (LVAS) with PTFE filters. Sample was collected for 7 days x 24 hours. Heavy metals in PM2.5 dust were characterized using ED-XRF. Calculation of non-carcinogenic and carcinogenic health risks was only performed on metals classified as Hazardous Air Pollutants (HAPs). The average concentration of PM2.5 during the measurement period was 59,10±9,10 μg/m3, exceeding the daily ambient air quality standard based on PP No.22 of 2021 which is> 55μg/m3. The risk of non-carcinogenicity is expressed in Health Index (HI) values. The heavy metals considered in determining non-carcinogenic risk are As, Cd, Cr, Pb, Mn, Ni, Se, Fe, Zn, Si, and Sb as well as the crustal elements Si and Fe. Non-carcinogenic risk associated with exposure to heavy metals in PM2.5 showed HI<1 for both children and adults. This indicates that the exposure to heavy metals in PM2.5 around the Dayeuhkolot industrial area is at an acceptable risk level. HI value for heavy metal exposure for children was 0.34±0.17 and 0.42±0.28 for adults. In estimating the carcinogenic risk value, elements taken into account include As, Cd, Cr, Ni and Pb. Carcinogenic risk in both children and adults showed ECR>10-6 of 4.5×10-5 and 2.1×10-4, respectively. This indicates that there is an unsafe health risk that can potentially cause carcinogenic effects in the population around the Dayeuhkolot industrial area The results of this study can be used as a reference database for establishing policies related to air quality in Bandung Regency.

Assessment of Particle Matter Pollution during Post-Earthquake Debris Removal in Adiyaman City

Severe earthquakes in the world and in Turkey can cause great loss of life and property, environmental problems and health problems. In addition to the loss of life and property, earthquakes are closely related to ecosystems, air, water, and soil pollution. Particularly in post-earthquake debris removal, very large amounts of particulate matter are released and may have negative effects on the health of the local population. This study aimed to detect two types of particle matter pollution during debris removal in 25 different locations in Adiyaman City using a CEM DT 9880 particle matter measuring device in May and August 2023. PM2.5 and PM10 measurements, which have a significant impact on human health, were conducted in the field. The obtained data were analyzed using the Inverse Distance Weighting (IDW) method in ArcGIS 10.7 software. Results showed that the highest particle matter pollution was identified in neighborhoods with extensive demolition. The highest PM2.5 pollution values were recorded in Barbaros Hayrettin, Hoca Omer, Yesilyurt, and Varlik neighborhoods, while the lowest was observed in Altinsehir and Yunus Emre neighborhoods with minimal demolition. As for PM10 pollution, the highest levels were observed in Alitasi, Barbaros Hayrettin, Sumerevler, and Hoca Omer neighborhoods, while the lowest was detected in Yunus Emre and Yesilyurt neighborhoods. Green areas and their surroundings in the field exhibited lower levels of PM pollution compared to other areas.

Effects of atmospheric pollution on human health in Port Harcourt: Its implication on urban planning

This study examined the health implication of atmospheric pollution in Port Harcourt. The study adopted both experimental research design and ex-post facto designs. This involved direct field measurements of air pollutants (Sulphur (IV) Oxide, Nitrogen Oxide, Carbon Monoxide, and PM10) and archival medical data of air borne diseases in Port Harcourt. The study area was stratified into four zones using existing land use types. In each of the four zones, three most heavily congested traffic intersections were selected for monitoring the air pollutants. The data generated were analysed using multiple regression statistical tool at 0.05 level of significance. The study revealed that the concentration of air pollutants measured in parts per million for SO2 (0.24), NO2 (0.06), CO (33.1) and PM10 (2.65) in Port Harcourt metropolis exceeded WHO standards for SO2 (±0.00-0.01), NO2 (±0.03-0.06), CO (±3-10) and PM10 (±0.9-1.12). The study revealed that air borne diseases were on the increase in Port Harcourt metropolis. During the rainy season, there was a low prevalence of Air borne diseases in Port Harcourt and this could be attributed to the rainfall which reduces dust and fine particles. At F values of 8.59 and 10.871 respectively, SO2, and PM10 had a significant effect on the occurrence of air borne diseases in Port Harcourt metropolis at P<0.05. As such, SO2, and PM10 gases were responsible for the increase in cardiovascular diseases, reduced lung function, asthma, irritation of the eyes, cough, nausea in Port Harcourt metropolis. To mitigate the effects of atmospheric pollution on human health, urban planning strategies should focus on promoting sustainable transportation options (such as public transit, cycling, and walking), increasing green spaces and planting trees to improve air quality, promoting energy-efficient buildings, and implementing regulations to reduce emissions from industrial sources. Incorporating measures to improve air quality into urban planning decisions can help create healthier and more livable cities for residents.

Results of expedition measurements of PM10, PAHs and mercury above the water area of Lake Baikal in August 2023

As a continuation of regular research to obtain information about mechanisms and sources of air pollution above the water area of Lake Baikal, we present the results of the expeditionary studies on the concentrations of РМ10, polycyclic aromatic hydrocarbons and gaseous elemental mercury in the near-water layer of the atmosphere above Lake Baikal in August 2023. On the route of the vessel along the perimeter of the lake, the concentrations of pollutants in the near-water atmosphere increased near the local sources of air pollution located on the coast of the southern basin (Listvyanka, Slyudyanka and Baikalsk) as well as at the source of the Angara River with the northwesterly transport from the industrial cities of the Baikal region. Over the study period, the РМ10 concentrations averaged 6.0 µg/‌m3, PAHs–1.1 ng/m3, and gaseous elemental mercury–0.75 ng/m3, which was lower than the values recorded during wildfires between 2016 and 2020 in some areas of Siberia. The resulting concentrations of the investigated air components did not exceed air quality standards. Pairwise correlations during the study period were high between РМ10 and PAHs (0.71) and low between PAHs and mercury (0.21).

Long-term exposure to PM10 and respiratory health among Parisian subway workers

Exposure to ambient PM10 may increase the risk of chronic obstructive pulmonary disease (COPD) and lung function decline. We evaluated the long-term exposure to PM10 and its relationship with COPD prevalence and lung function in Parisian subway workers.Participants were randomly selected from a 15,000-subway worker cohort. Individual annual external exposure to PM10 (ePM10) was estimated using a company-specific job-exposure-matrix based on PM10 measurements conducted between 2004 and 2019 in the Parisian subway network. Mean annual inhaled PM10 exposure (iPM10) was modeled as function of ePM10 exposure, inhalation rate, and filtration efficiency of the respiratory protection used. COPD diagnosis was performed in March–May 2021 based on post-bronchodilator spirometry. The relationship between iPM10 and outcomes was assessed using logistic and linear regression models, adjusted for exposure duration and potential confounders.Amongst 254 participants with complete data, 17 were diagnosed as COPD. The mean employment duration was 23.2 ± 7.3years, with annual mean ePM10 of 71.8 ± 33.7 μg/m3 and iPM10 of 0.59 ± 0.27 μg/shift, respectively. A positive but statistically non-significant association was found for COPD prevalence with iPM10 (OR = 1.034, 95%-CI = 0.781; 1.369, per 100 ng/shift) and ePM10 (OR = 1.029, 95%-CI = 0.879; 1.207, per 10 μg/m3). No decline in lung function was associated with PM10 exposure. However, forced expiratory volume during the first second and forced vital capacity lower than normal were positively associated with exposure duration (OR = 1.125, 95%-CI = 1.004; 1.260 and OR = 1.171, 95%-CI = 0.989; 1.386 per year, respectively). Current smoking was strongly associated with COPD prevalence (OR = 6.85, 95%-CI = 1.87; 25.10) and most lung function parameters.This is the first study assessing the relationship between long-term exposure to subway PM10 and respiratory health in subway workers. The risk estimates related with subway PM10 exposure are compatible with those related to outdoor PM10 exposure in the large recent studies. Large cohorts of subway workers are necessary to confirm these findings.

PM1, PM2.5 and PM10 size fraction distribution under steady-state conditions in a walk-in type 222Rn calibration chamber facility.

Attachment of 222Rn progenies, upon their formation, to the atmospheric aerosols and inhalation of these radioactive aerosols causes inhalation dose to the human being. Aerosols have the characteristics of small particle size, long-time suspension and long-distance transmission and easy access to the deep respiratory tract. Aerosols are responsible for viral infection risk such as the recent worldwide pandemic caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2, or COVID-19). Understanding the formation and behaviour of aerosols in a confined environment in various human habitations is essential to combat such detrimental exposures. Experiments have been performed to study the distribution of aerosol size fractions in the walk-in type 222Rn calibration chamber. The real-time applied particle technology monitors (APT-Maxima stationary monitors) were used for the simultaneous measurements of PM1, PM2.5, and PM10 size fractions. The variation of the mass densities (μgm-3) of different size fractions at different positions inside the chamber was monitored by placing APTs. The PM1, PM2.5, and PM10 sizes fractions were distributed homogeneously within the chamber volume and the concentration ratios of these fractions were 1:1.5:1.6 for concentration values of < 1500μgm-3, and 1:7:9 for the concentration values of > 1500μgm-3.

Molecular and Elemental Tracers‐Based Receptor Modeling of PM2.5 in Suburban Hong Kong With Hourly Time‐Scale Air Quality Considerations

AbstractContinuing control efforts in recent decade have notably brought down fine‐particulate‐matter (PM2.5) pollution to compliance with the annual average air quality objective in Hong Kong. However, short‐term (several hours to few days) PM2.5 pollution sporadically occurred in winter and has become a major focus of attention, calling research in characterizing sources and their variations at hourly timescale. This study reports hourly measurements of PM2.5 and its chemical speciation, including molecular and elemental tracers in suburban Hong Kong in 2020 winter. Hourly PM2.5 was 20.3 ± 7.33 μg m−3, dominated by organics and sulfate. We deployed tracer‐based source apportionment using positive matrix factorization, which resolved six secondary and seven primary sources. Sulfate‐rich and nitrate‐rich factors were the leading PM2.5 contributors. Variation in source contributions under different air masses revealed the Pearl River Delta region and coastal areas to the north are main origins. Elevation in secondary sources was the driving factor in causing high PM2.5 polluted hours. During Chinese New Year holiday, firework emissions partially offset the reductions in anthropogenic sources, even leading to an increased PM2.5. Hour‐by‐hour examination of most polluted and firework event hours enhanced understanding on dynamic variations of haze and firework burning evolution. The mass concentration of firework‐derived PM2.5 was notably lower under “prohibition” than “restriction” control scenario (avg. 3.5 vs. 8.4 μg m−3). Our results highlight the effectiveness of tracer‐based source apportionment in revealing hourly PM2.5 source variations and the necessity of regional joint management to lessen the severity of episodic PM2.5 pollution and health risks.

Integrating Augmented In Situ Measurements and a Spatiotemporal Machine Learning Model To Back Extrapolate Historical Particulate Matter Pollution over the United Kingdom: 1980-2019.

Historical PM2.5 data are essential for assessing the health effects of air pollution exposure across the life course or early life. However, a lack of high-quality data sources, such as satellite-based aerosol optical depth before 2000, has resulted in a gap in spatiotemporally resolved PM2.5 data for historical periods. Taking the United Kingdom as an example, we leveraged the light gradient boosting model to capture the spatiotemporal association between PM2.5 concentrations and multi-source geospatial predictors. Augmented PM2.5 from PM10 measurements expanded the spatiotemporal representativeness of the ground measurements. Observations before and after 2009 were used to train and test the models, respectively. Our model showed fair prediction accuracy from 2010 to 2019 [the ranges of coefficients of determination (R2) for the grid-based cross-validation are 0.71-0.85] and commendable back extrapolation performance from 1998 to 2009 (the ranges of R2 for the independent external testing are 0.32-0.65) at the daily level. The pollution episodes in the 1980s and pollution levels in the 1990s were also reproduced by our model. The 4-decade PM2.5 estimates demonstrated that most regions in England witnessed significant downward trends in PM2.5 pollution. The methods developed in this study are generalizable to other data-rich regions for historical air pollution exposure assessment.

A case study evaluating the performance of a cost-effective optical particle counter coupled with a humidity compensation approach for ambient air monitoring of particulate matter

The spatial monitoring of submicron particles has become an essential issue due to their negative effects on human health. However, the use of high-cost and high-grade measurement instruments is a challenging investment cost. Thus, a cost-effective optical particle counter (OPC), which is improved measurement quality, has become a good candidate. In this study, two cost-effective OPCs, coupled with a heated inlet tube to reduce the effect of humidity on its measurements, were applied in the field to measure ambient PM10, PM2.5, and PM1 over 1 month. Their 1-h-average and 24-h-average data were compared with those obtained from a reference-grade OPC and a beta attenuation monitor (BAM). In particular, the correlations between the measurement data obtained from them, the differences in the mean values of these data, and the relative errors were evaluated. The PM2.5 data obtained from cost-effective OPCs were comparable to those from BAM at even under high humidity conditions, except for rainy days. The data obtained from the cost-effective OPCs also showed good correlations and low relative errors (i.e., < 7%) compared to the reference-grade OPC, with no significant difference in mean values in terms of the PM2.5 and PM1 data. Although the measurement of PM10 by the cost-effective OPCs showed lower quality than PM2.5 and PM1, the relative errors were still acceptable (i.e., < 18%) compared with those in other studies. Therefore, the cost-effective OPC coupled with a heated inlet tube has the potential to serve as a real-time monitoring instrument for ambient PM2.5 and PM1.

Effect of environmental conditions on the performance of a low-cost atmospheric particulate matter sensor

Continuous measurements of PM10, PM2.5, and PM1 concentrations were carried out by collocating a GRIMM Aerosol Laser Spectrometer model 11-C as a reference instrument and three Plantower PMS7003 low-cost sensor (LCS) from June 11, 2019, to April 23, 2020, in a residential/commercial area of the city of Santiago de Chile. Completeness, precision, linearity, bias, and error metrics were analyzed to evaluate the performance of PMS7003. Linear regression and quadratic polynomial models were proposed to correct the concentrations provided by LCS based on the environmental variables studied. The performance of the LCS was outstanding for the PM1 fraction, obtaining R2 = 0.98, slope = 1.1. PM2.5 and PM10 concentrations were underestimated in drier and warmer summer conditions and slightly overestimated in colder and wetter winter conditions. In the case of PM2.5, three correction models were proposed, two of which considered four possible conditions based on the relative humidity and temperature to identify their influence on the LCS performance, achieving R2 values of 0.869 and 0.875, respectively. The LCS showed low linearity and bias value for PM10; the correction model for this PM fraction with the highest value in the metrics obtained an R2 = 0.630, therefore its use is recommended only for educational purposes.

Withstanding the test of time: Morning versus afternoon/evening urine protein-to-creatinine ratios in preeclampsia

ObjectiveThere are mixed findings regarding time preference for measuring spot urine protein to creatinine ratios (UPCR) in renal patients but no such literature among pregnant patients. We compare AM versus PM measurements for UPCR among pregnant patients with preeclampsia. Study designThis retrospective study included 163 patients diagnosed with preeclampsia. Laboratory tests of UPCR, urine specificity gravity, and uric acid were collected for these patients during the morning (AM) 12:00 AM (00:00) through 11:59 AM (11:59) and afternoon/evening (PM) 12:00 PM (12:00) through 11:59 PM (23:59). Main outcome measuresOutcomes were UPCR percentages indicative of preeclampsia, UPCR median values, abnormal uric acid, and normal urine specific gravity indicative of a quality sample for measuring UPCR. ResultsUPCR ≥ 0.3 indicative of preeclampsia significantly differed (p < 0.001) where the AM group (76.7 %) had a greater percentage than the PM group (52.8 %). Median UPCR significantly differed (p < 0.001) where the AM group had a greater median (0.44) than the PM group (0.32). None of the uric acid or urine specific gravity comparisons significantly differed between the AM and PM groups. Similar patterns occurred for subgroups of those with hypertension, nulliparous, and preeclampsia with severe features. ConclusionWe found that UPCR had greater median values and more values indicative of preeclampsia for AM measurements than PM measurements. Clinicians who use spot urine measurements and not 24-hour urine measurements should preferably measure UPCR in the AM rather than the PM.

Analisis Tingkat Pencemaran Lingkungan Permukiman Di Sekitar Pasar Mangkang Kota Semarang

Mangkang Market in Semarang City is a market with high economic activity. Mangkang Market is located on the pantura road that connects Semarang City with Kendal Regency, so it has high mobility, potentially causing noise and PM 2.5 air pollution in settlements around the market. Market activities also have the potential for water pollution in Kali Bakti. This study aims to determine the level of environmental pollution of settlements living around Mangkang Market. For this purpose, noise measurements, PM 2.5 air quality and water conditions in Kali Bakti were conducted. Measurement of surface water by taking water samples in Kali Bakti was carried out to measure the level of drainage water quality which is a place for domestic wastewater disposal. The water condition in Kali Bakti was measured in the laboratory of Semarang City Environmental Agency. The method in this study uses a descriptive quantitative approach by categorizing based on class or level. The result of noise measurement using Sound Level meter and formula is that the settlement noise is included in the low level of 52.4 dB from the standard 55 dB. While the measurement of PM 2.5 air quality is included in the high pollution category, namely 27 µg / Nm3, from the standard standard of 25 µg / Nm3 based on WHO. And laboratory checks of water in Kali Bakti are included in the medium level of pollution, namely IPj 2,151370942.