Fixed-site Monitoring Research Articles

Personal exposure to black carbon in Stockholm, Sweden, compared to fixed-site monitoring and dispersion modelling

INTRODUCTION AND AIM Short-term studies of health effects from ambient air pollution usually rely on fixed site monitoring data or spatio-temporal models for exposure characterization, but the relation to personal exposure is often not known. We aimed to explore this relation for black carbon (BC) in central Stockholm. METHODS Families (n=36) with an infant, one parent working and one parent on leave, agreed to perform personal measurements of BC for the parents, with battery-operated aethalometers for 7 days. Routine monitoring data were from rural background (RB) and urban background (UB). Outdoor levels at home and work were estimated in 24h periods by dispersion modelling with real-time meteorological data. Global radiation, air pressure, precipitation, temperature, and wind speed data were achieved from an urban background station. All families lived within 4 km from the city center. RESULTS The average level of 24h personal BC was 370 (s.d. 200) ng/m3 for parents on leave, and 357 (s.d. 175) ng/m3 for working parents. The corresponding fixed-site monitoring observations were 148 (s.d. 139) at RB and 317 (s.d. 149) at UB. Modelled BC at home and at work were 493 (s.d. 228) and 331 (s.d. 173) ng/m3, respectively. UB, RB and air pressure explained only 21% of personal 24h BC variability for parents on leave and 25% for working parents. Modelled home BC and air pressure explained 23% of personal BC, and adding modelled BC at work increased the explanation to 34% for the working parents. CONCLUSION Both routine monitoring and modeled data explained less than 35% of variability in personal 24h observations of BC exposure. Any associated short-term health effects are likely to be underestimated in studies using such exposure data. KEYWORDS Black carbon, Personal exposure, Dispersion modelling

Effects of plastic film mulching on the spatiotemporal distribution of soil water, temperature, and photosynthetic active radiation in a cotton field.

Plastic film mulching (PFM) affects the spatiotemporal distribution of soil moisture and temperature, which in turn affects cotton growth and the spatiotemporal distribution of canopy photosynthetically active radiation (PAR). Due to the spatial heterogeneity of soil moisture, temperature and limited monitoring methods, the issues such as relatively few sampling points and long sampling intervals in most existing studies prevent the accurate quantification of spatiotemporal changes in moisture and temperature along soil profile. To investigate the effects of PFM on spatiotemporal changes in soil moisture, temperature, and canopy PAR in cotton fields, two field trials of plastic film-mulched (M) and nonmulched (NM) cultivations were performed in 2018 and 2019. The grid method was used for the soil information continuous monitoring and multiple-time fixed-site canopy PAR monitoring during the duration of cotton growth. Two-year field trial data showed that, M cultivation increased soil moisture by approximately 13.6%–25% and increased temperature by 2–4 °C in the 0–50 cm soil layer before the first irrigation (June 20) and by 1–2 °C in the 70–110 cm soil layer, compared with NM cultivation. In addition, the temperature difference between the two treatments gradually decreased with the increase in irrigation and air temperature. The M treatment reached the peak PAR interception rate 10 days earlier than the NM treatment. In 2018 and 2019, the PAR peak value under the M treatment was 4.62% and 1.8% higher than that under the NM treatment, respectively, but the PAR interception rate was decreased rapidly in the late growth stage. Overall, PFM had an effect on soil moisture retention during the whole growth period and greatly increased the soil temperature before budding stage, thus promoted the early growth of cotton. Considering this, we suggest that the irrigation quota and frequency could be appropriately decreased in the case of plastic film mulching cultivation. For nonmulching cultivation, the irrigation quota and frequency should be increased, and it is necessary to take measures to improve the soil temperature before middle July.

Assessment of the impact of sensor error on the representativeness of population exposure to urban air pollutants.

For the monitoring of urban air pollution, smart sensors are often seen as a welcome addition to fixed-site monitoring (FSM) networks. Due to price and simple installation, increases in spatial representation are thought to be achieved by large numbers of these sensors, however, a number of sensor errors have been identified. Based on a high-resolution modelling system, up to 400 pseudo smart sensors were perturbated with the aim of simulating common sensor errors and added to the existing FSM network in Hong Kong, resulting in 1200 pseudo networks for PM2.5 and 1040 pseudo networks for NO2. For each pseudo network, population-weighted area representativeness (PWAR) was calculated based on similarity frequency. For PM2.5, improvements (up to 16%) to the high baseline representativeness (PWAR=0.74) were achievable only by the addition of high-quality sensors and favourable environmental conditions. The baseline FSM network represents NO2 less well (PWAR=0.52), as local emissions in the study domain resulted in high spatial pollution variation. Due to higher levels of pollution (population-weighted average 37.3ppb) in comparison to sensor error ranges, smart sensors of a wider quality range were able to improve network representativeness (up to 42%). Marginal representativeness increases were found to exponentially decrease with existing sensor number. The quality and maintenance of added sensors had a stronger effect on overall network representativeness than the number of sensors added. Often, a small number of added sensors of a higher quality class led to larger improvements than hundreds of lower-class sensors. Whereas smart sensor performance and maintenance are important prerequisites particularly for developed cities where pollutant concentration is low and there is an existing FSM network, our study shows that for places with high pollutant variability and concentration such as encountered in some developing countries, smart sensors will provide benefits for understanding population exposure.

Fine-Grained Urban Air Quality Mapping from Sparse Mobile Air Pollution Measurements and Dense Traffic Density

Urban air quality mapping has been widely applied in urban planning, air pollution control and personal air pollution exposure assessment. Urban air quality maps are traditionally derived using measurements from fixed monitoring stations. Due to high cost, these stations are generally sparsely deployed in a few representative locations, leading to a highly generalized air quality map. In addition, urban air quality varies rapidly over short distances (<1 km) and is influenced by meteorological conditions, road network and traffic flow. These variations are not well represented in coarse-grained air quality maps generated by conventional fixed-site monitoring methods but have important implications for characterizing heterogeneous personal air pollution exposures and identifying localized air pollution hotspots. Therefore, fine-grained urban air quality mapping is indispensable. In this context, supplementary low-cost mobile sensors make mobile air quality monitoring a promising alternative. Using sparse air quality measurements collected by mobile sensors and various contextual factors, especially traffic flow, we propose a context-aware locally adapted deep forest (CLADF) model to infer the distribution of NO2 by 100 m and 1 h resolution for fine-grained air quality mapping. The CLADF model exploits deep forest to construct a local model for each cluster consisting of nearest neighbor measurements in contextual feature space, and considers traffic flow as an important contextual feature. Extensive validation experiments were conducted using mobile NO2 measurements collected by 17 postal vans equipped with low-cost sensors operating in Antwerp, Belgium. The experimental results demonstrate that the CLADF model achieves the lowest RMSE as well as advances in accuracy and correlation, compared with various benchmark models, including random forest, deep forest, extreme gradient boosting and support vector regression.

A Case-Crossover Analysis of the Association between Exposure to Total PM2.5 and Its Chemical Components and Emergency Ambulance Dispatches in Tokyo

A limited number of studies have investigated the association between short-term exposure to PM2.5 components and morbidity. The present case-crossover study explored the association between exposure to total PM2.5 and its components and emergency ambulance dispatches, which is one of the indicators of morbidity, in the 23 Tokyo wards. Between 2016 and 2018 (mean mass concentrations of total PM2.5 13.5 μg/m3), we obtained data, from the Tokyo Fire Department, on the daily cases of ambulance dispatches. Fine particles were collected at a fixed monitoring site and were analyzed to estimate the daily mean concentrations of carbons and ions. We analyzed 1038301 cases of health-based all-cause ambulance dispatches by using a conditional logistic regression model. The average concentrations of total PM2.5 over one and the previous day were positively associated with the number of ambulance dispatches. In terms of PM2.5 components, the percentage increase per interquartile range (IQR) increase was 0.8% for elemental carbon (IQR = 0.8 μg/m3; 95% CI = 0.3-1.3%), 0.9% for sulfate (2.1 μg/m3; 0.5-1.4%), and 1.1% for ammonium (1.3 μg/m3; 0.4-1.8%) in the PM2.5-adjusted models. This is the first study to find an association between some specific components in PM2.5 and ambulance dispatches.

Assessment of air pollution in the informal settlements of the Western Cape, South Africa


 
 
 
 Introduction: South Africa has the highest ambient air pollution exposure associated with morbidity in the Sub-Saharan region, accounting for a total number of 14356 confirmed cases of mortality on an annual basis. The study assessed air pollution exposure levels of Khayelitsha and Marconi-Beam neighbourhoods that are not monitored by the fixed-site monitoring station provided by the government.
 Materials and methods: Weekly ambient air pollution measurements of Particulate Matter less than 2.5 μm (PM2.5) and Nitrogen Dioxide (NO2) were collected at households in neighbourhoods of Khayelitsha and Marconi-Beam during the summer and winter seasons. PM2.5 measurements were collected using Mesa Labs GK2.05 (KTL) cyclone attached to a GilAir Plus air sampling pump. Gases of NO2 were measured using passive diffusive samplers. Data were recorded on a Microsoft Excel 2016 spreadsheet. Statistical analyses were performed using IBM SPSS Statistics 28.0. The outcome of the seasonal exposure levels will be compared with the South African ambient air quality standards to ascertain the risk of potential exposure to significant levels of PM2.5 and NO2 that are hazardous to human health.
 Results: The results suggest that summer NO2 concentrations in the Khayelitsha neighbourhood ranged between (0 and 28 μg/m3), while in winter NO2 concentrations nearly doubled. A similar trend was observed regarding PM2.5 behaviour with summer overall exposure level of 7 μg/m3 and 13 μg/m3 during winter.
 Conclusion: Whilst there are no legislative guidelines to compare the measured weekly average results, the concentrations were still lower than the World Health Organization (WHO), and South African air quality standards values for PM2.5 and NO2 pollutants.
 
 
 

Development of methods for citizen scientist mapping of residential woodsmoke in small communities

BackgroundResidential wood burning is a major source of fine particulate matter (PM2.5) during winter and a leading contributor to air pollution. Exposure to woodsmoke PM2.5 is associated with many health effects, so it is important to characterize the magnitude and spatial variability in exposures. However, high infrastructure and maintenance costs of regulatory monitoring stations limit their spatial resolution and make monitoring infeasible for many small communities where woodsmoke may be prevalent. MethodsMobile monitoring was conducted with a nephelometer and multi-wavelength aethalometer, capable of identifying woodsmoke PM2.5, to capture spatially resolved data. This Combined Aethalometer and Nephelometer for Assessment of Woodsmoke (CANAW) method was evaluated in three pairs of communities in British Columbia, Canada. Measurements were also taken at fixed-site monitoring stations. Light scattering measured by a nephelometer (Bsp) was compared with gravimetric filter-based and beta-attenuation measures of PM2.5. The difference in absorbance of 370 nm and 880 nm wavelengths as measured by an aethalometer (delta C), was compared with the chemical woodsmoke tracer levoglucosan. ResultsFixed site measurements of Bsp and delta C were comparable with established methods of monitoring PM2.5 and woodsmoke, respectively. Correlations in each tested relationship across all locations were high (r ≥ 0.93 in all cases). Mobile monitoring captured high spatial variation in woodsmoke PM2.5 and maps of average concentrations during monitoring were created to identify woodsmoke hotspots. ConclusionFollowing the successful implementation of the mobile CANAW method, training materials were created and tested with lay volunteers along with an online mapping application. Volunteers were able to effectively operate the equipment, collect valuable data on woodsmoke concentrations, and map spatial patterns across their communities using the application. The CANAW method is a valuable option for advancing cost-effective data collection for residential woodsmoke in otherwise unmonitored communities, and to add spatial context to existing monitoring networks.

Methods and development trend for the measurement of plant species diversity in grasslands.

Plant species diversity is one of the critical factors for maintaining multi-function and stability of terrestrial ecosystem. We reviewed the traditional methods for measuring plant species diversity of grassland (PSDG), and then introduced the new ideas and methods used for PSDG monitoring. Traditionally, PSDG monitoring depended heavily on ground-based investigation, which usually required large amounts of time, labor, and cost, and therefore was only suitable for small scale investigation. Grassland plant species were typically small in size and highly mixed. It was difficult to identify and measure by remote sensing due to the limitation of resolution. Consequently, most studies on PSDG were based on remote-sensing retrieval or habitat simulation. Characterized with high spatial-temporal resolution, flexible and low cost, the unmanned aerial vehicle (UAV) technology was regarded as the bridge between ground-based investigation and satellite remote sensing. It could be the breakthrough for monitoring PSDG accurately at large scales. In the future, we should establish PSDG monitoring network by combining the fixed monitoring sites and dynamic monitoring sites of UAV and satellite remote sensing, and integrating UAV and automatic target recognition organically.

Community-Engaged Use of Low-Cost Sensors to Assess the Spatial Distribution of PM2.5 Concentrations across Disadvantaged Communities: Results from a Pilot Study in Santa Ana, CA.

PM2.5 is an air pollutant that is widely associated with adverse health effects, and which tends to be disproportionately located near low-income communities and communities of color. We applied a community-engaged research approach to assess the distribution of PM2.5 concentrations in the context of community concerns and urban features within and around the city of Santa Ana, CA. Approximately 183 h of one-minute average PM2.5 measurements, along with high-resolution geographic coordinate measurements, were collected by volunteer community participants using roughly two dozen low-cost AtmoTube Pro air pollution sensors paired with real-time GPS tracking devices. PM2.5 varied by region, time of day, and month. In general, concentrations were higher near the city’s industrial corridor, which is an area of concern to local community members. While the freeway systems were shown to correlate with some degree of elevated air pollution, two of four sampling days demonstrated little to no visible association with freeway traffic. Concentrations tended to be higher within socioeconomically disadvantaged communities compared to other areas. This pilot study demonstrates the utility of using low-cost air pollution sensors for the application of community-engaged study designs that leverage community knowledge, enable high-density air monitoring, and facilitate greater health-related awareness, education, and empowerment among communities. The mobile air-monitoring approach used in this study, and its application to characterize the ambient air quality within a defined geographic region, is in contrast to other community-engaged studies, which employ fixed-site monitoring and/or focus on personal exposure. The findings from this study underscore the existence of environmental health inequities that persist in urban areas today, which can help to inform policy decisions related to health equity, future urban planning, and community access to resources.

Inter- and Intra-Individual Variability of Personal Health Risk of Combined Particle and Gaseous Pollutants across Selected Urban Microenvironments

Exposure surrogates, such as air quality measured at a fixed-site monitor (FSM) or residence, are typically used for health estimates. However, people spend various amounts of time in different microenvironments, including the home, office, outdoors and in transit, where they are exposed to different magnitudes of particle and gaseous air pollutants. Health risks caused by air pollution exposure differ among individuals due to differences in activity, microenvironmental concentration, as well as the toxicity of pollutants. We evaluated individual and combined added health risks (AR) of exposure to PM2.5, NO2, and O3 for 21 participants in their daily life based on real-world personal exposure measurements. Exposure errors from using surrogates were quantified. Inter- and intra-individual variability in health risks and key contributors in variations were investigated using linear mixed-effects models and correlation analysis, respectively. Substantial errors were found between personal exposure concentrations and ambient concentrations when using air quality measurements at either FSM or the residence location. The mean exposure errors based on the measurements taken at either the FSM or residence as exposure surrogates was higher for NO2 than PM2.5, because of the larger spatial variability in NO2 concentrations in urban areas. The daily time-integrated AR for the combined PM2.5, NO2, and O3 (TIARcombine) ranged by a factor of 2.5 among participants and by a factor up to 2.5 for a given person across measured days. Inter- and intra-individual variability in TIARcombine is almost equally important. Several factors were identified to be significantly correlated with daily TIARcombine, with the top five factors, including PM2.5, NO2 and O3 concentrations at ‘home indoor’, O3 concentrations at ‘office indoor’ and ambient PM2.5 concentrations. The results on the contributors of variability in the daily TIARcombine could help in targeting interventions to reduce daily health damage related to air pollutants.

Associations of Carbonaceous Compounds and Water-Soluble Inorganic Ions in Ambient PM2.5 with Renal Function in Older Individuals: The China BAPE Study.

Exposure to fine particulate matter (PM2.5) is proven to be associated with a decline in renal function. However, few studies have explored the acute renal damage from carbonaceous compounds and water-soluble inorganic ions (WSIIs), which constitute the bulk of total PM2.5 mass. We examined the acute effect of these constituents of ambient PM2.5 on renal function in older Chinese individuals. Seventy-one healthy people aged 60-69 years from Jinan, China, were enrolled and visited monthly and asked to complete survey questionnaires, undergo physical exams, and provide blood samples. The hourly concentrations of organic carbon, elemental carbon (EC), and WSIIs in ambient PM2.5 were collected from a fixed-site monitoring station. The association between PM2.5 constituents and estimated glomerular filtration rate (eGFR) was evaluated using linear mixed-effects models after controlling for a series of covariates. We observed that ambient carbonaceous compounds and WSIIs were associated with a significant decline in renal function. The interquartile range increased in the 24 h moving average of carbonaceous compounds, and WSIIs in ambient PM2.5 were associated with -13.11% [95% confidence interval (95% CI): -19.49, -6.21%] to -0.81% (95% CI: -4.17, 2.67%) changes in eGFR. We found significant associations between EC, chlorine (Cl-), sodium (Na+), and magnesium (Mg2+) and eGFR in single-pollutant, constituent-PM2.5, and residual-constituent models with a lag period of 0-24 h. This study demonstrated that carbonaceous compounds and WSIIs in PM2.5 were inversely associated with renal function.

Spatial matrix completion for spatially misaligned and high‐dimensional air pollution data

AbstractIn health‐pollution cohort studies, accurate predictions of pollutant concentrations at new locations are needed, since the locations of fixed monitoring sites and study participants are often spatially misaligned. For multi‐pollution data, principal component analysis (PCA) is often incorporated to obtain low‐rank (LR) structure of the data prior to spatial prediction. Recently developed predictive PCA modifies the traditional algorithm to improve the overall predictive performance by leveraging both LR and spatial structures within the data. However, predictive PCA requires complete data or an initial imputation step. Nonparametric imputation techniques without accounting for spatial information may distort the underlying structure of the data, and thus further reduce the predictive performance. We propose a convex optimization problem inspired by the LR matrix completion framework and develop a proximal algorithm to solve it. Missing data are imputed and handled concurrently within the algorithm, which eliminates the necessity of a separate imputation step. We review the connections among those existing methods developed for spatially misaligned multivariate data, and show that our algorithm has lower computational burden and leads to reliable predictive performance as the severity of missing data increases.

Short-term ozone exposure and metabolic status in metabolically healthy obese and normal-weight young adults: A viewpoint of inflammatory pathways

Unhealthy metabolic status increases risks of cardiovascular and other diseases. This study aims to explore whether there is a link between O3 and metabolic health indicators through a viewpoint of inflammatory pathways. 49 metabolically healthy normal-weight (MH-NW) and 39 metabolically healthy obese (MHO) young adults aged 18–26 years were recruited from a panel study with three visits. O3 exposure were estimated based on fixed-site environmental monitoring data and time-activity diary for each participant. Compared to MH-NW people, MHO people were more susceptible to the adverse effects on metabolic status, including blood pressure, glucose, and lipid indicators when exposed to O3. For instance, O3 exposure was associated with significant decreases in high-density lipoprotein cholesterol (HDL-C), and increases in C-peptide and low-density lipoprotein cholesterol (LDL-C) among MHO people, while only weaker changes in HDL-C and LDL-C among MH-NW people. Mediation analyses indicated that leptin mediated the metabolic health effects in both groups, while eosinophils and MCP-1 were also important mediating factors for the MHO people. Although both with a metabolically healthy status, compared to normal-weight people, obese people might be more susceptible to the negative effects of O3 on metabolic status, possibly through inflammatory indicators such as leptin, eosinophils, and MCP-1.

Surface ozone monitoring and policy: A geospatial decision support tool for suitable location of monitoring stations in urban areas

Fixed site monitoring is the primary method of measuring surface ozone pollution for health advisories and pollutant reduction, but the spatial scale may not reflect the current population distribution or its future growth. Moreover, formal methods for the placement of ozone monitoring sites within populations regions omit important spatial criteria producing monitoring locations that could unintentionally bias the exposure burden. Because ozone pollution endangers human health, triggering shortness of breath, causing asthma attacks and mortality, a need exists for assessing the spatial representativeness and data gaps of existing pollution monitors and to evaluate future placement strategies of additional monitors. A new metric, the potency index, for assessing the placements of monitors in relation to population distribution was developed. This index was used to evaluate the configuration of the ozone pollution monitoring network in relation to the population distribution in Dallas-Fort Worth (DFW). Location-allocation models were used to optimize future sensor quantity and placement. Finally, we propose the development of a decision support system that uses evaluation and optimization methods to improve air pollution monitoring objectives.

Application of a mobile laboratory using a selected-ion flow-tube mass spectrometer (SIFT-MS) for characterisation of volatile organic compounds and atmospheric trace gases

Abstract. Over the last 2 decades, the importance of emissions source types of atmospheric pollutants in urban areas has undergone significant change. In particular, there has been a considerable reduction in emissions associated with road vehicles. Understanding the role played by different source sectors is important if effective air pollution control is to be achieved. Current atmospheric measurements are made at fixed monitoring sites, most of which do not include the measurement of volatile organic compounds (VOCs), so our understanding of the temporal and spatial variation of pollutants is limited. Here we describe the application of a mobile laboratory using a selected-ion flow-tube mass spectrometer (SIFT-MS) and other trace gas instrumentation to provide on-road, high-spatial- and temporal-resolution measurements of CO2, CH4, VOCs and other trace gases. We then illustrate the potential of this platform for developing source characterisation methods that account for the similarity in correlation between species. Finally, we consider the benefits of high-spatial- and temporal-resolution measurements in characterising different types of sources, which would be difficult or impossible for single-species studies.

Glucose metabolism disorder enhanced the changes in cardiovascular function associated with exposure to ambient air particulate matter: a panel study

BACKGROUND AND AIM: Exposure to ambient air particulate matter (PM) is associated with increasing risk to cardiovascular diseases, but the underlying mechanisms remain unclear. This study aims to assess the effects of exposure to PM on indicators of cardiovascular function in a group of Beijing residents with and without pre-diabetes. METHODS: In a panel study (SCOPE) conducted in Beijing, China, 112 nonsmoking participants completed two to seven clinical visits. Indicators of cardiovascular function, including peripheral blood pressure, central arterial pressure, augmentation pressure normalized to a heart rate of 75 bpm (AP75), augmentation index normalized to a heart rate of 75 bpm (AIx75), ejection duration (ED), subendocardial viability ratio (SEVR), and reactive hyperemia index (RHI) were measured. Fine particles (PM₂.₅), ultrafine particles (UFP), accumulation-mode particles (AMP), and black carbon (BC) were monitored continuously at a fixed monitoring site. The associations between changes in cardiovascular function and moving average concentrations of PM during 1-7 day prior to clinical visits, and the modification of glucose metabolism status on such associations were examined with linear mixed-effects models. RESULTS:The changes in cardiovascular function associated with PM exposure differed significantly between participants with and without pre-diabetes. Among pre-diabetic participants, higher peripheral blood pressure and central arterial pressure were in significant association with UFP, AMP, or BC exposure, for example, an interquartile range increment in 7-day moving average BC exposure (4.8 μg/m³) was associated with 3.2% (95% confidence interval: 0.6%, 5.9%) increase in peripheral systolic blood pressure (p-SBP), while the associations among those without pre-diabetes were close to null or inverse. Additionally, positive associations in AP75 with BC exposure, and negative associations in SEVR with PM₂.₅ exposure were only shown among pre-diabetic participants. CONCLUSIONS:Glucose metabolism disorder may enhance the adverse impacts of exposure to PM on cardiovascular function. KEYWORDS: Particulate matter, cardiovascular function, pre-diabetes

Use of a LASSO approach to Identify ambient volatile organic compounds associated with emergency admissions for lower respiratory tract infection

BACKGROUND AND AIM: Existing evidence suggests that ambient volatile organic compounds (VOCs) may be associated with adverse respiratory outcomes, but it is unclear whether specific components may be responsible for triggering respiratory diseases. We aimed to examined which VOCs are associated with emergency admissions for lower respiratory tract infection (LRTI) based on a LASSO approach. METHODS: We obtained daily concentrations for 98 types of VOCs from two fixed-site monitoring stations located in Beijing. People who resided in Beijing for half a year or more and were hospitalized in local hospitals for the diagnosis of LRTI during the period of 2015 to 2016 were included. We used a LASSO approach to estimate specific VOC effects: (1) including all types of VOCs and fitting generalized linear models with a LASSO penalty function in a time-series framework using quasi-Poisson regression to identify which VOCs may be triggering LRTI; (2) including a specific VOC and fitting classic generalized linear models to estimate the associations with LRTI. RESULTS:There were 184,865 emergency admissions for LRTI during 2015 to 2016 in Beijing. Total VOC concentration ranged from 12.79ppb to 258.95ppb, of which alkanes account for about 38%, followed by alkenes (14%), and alkynes (7%). For LRTI, acetylene (C2H2), acrolein (C3H4O), 2,3-dimethylbutane (C6H14) and bromodichloromethane (CHBrCl2) were selected by the LASSO penalty function. Per IQR increase, short-term exposure to same-day C2H2 and C6H14 were associated with 1.90% (95%CI: 0.75, 3.07) and 2.07% (95%CI: 0.47, 3.70) change in LRTI, while C3H4O and CHBrCl2 were associated with 1.01% (95%CI: -0.24, 2.28) and -0.03% (95%CI: -0.75, 0.70) change in LRTI, respectively. CONCLUSIONS:Our study suggests that short-term exposure to C2H2 and C6H14 is associated with increased risk of LRTI emergency admissions. These specific components may reflect the role of traffic emission. Additional research is necessary to examine whether C3H4O and CHBrCl2 may affect LRTI. KEYWORDS: air pollution, volatile organic compounds, LASSO, respiratory emergency admissions

Associations between difference in anemia-related blood cell parameters and short-term exposure to ambient fine particles in Beijing elderly residents

BACKGROUND AND AIM: Anemia is a highly prevalent disease among elderly population with multiple adverse health outcomes. Particle exposure was a potentially risk factor of anemia. However, few studies have investigated the associations of particle exposure with anemia-related outcomes in the elderly, and the underlying mechanism is unclear. METHODS: Based on a panel study conducted between July 2016 and September 2017, anemia-related blood cell parameters, including red blood cell count (RBC), hemoglobin (HGB), hematocrit (HCT), mean corpuscular volume (MCV), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), and tumor necrosis factor α (TNF α), a marker of systemic inflammation, in serum samples were measured from 135 elderly participants at up to four clinical visits. Particulate pollutants—including particulate matter with an aerodynamic diameter of ≤ 2.5μm (PM2.5), black carbon (BC), ultrafine particles (UFPs), and accumulated-mode particles (Acc)—were continuously monitored at a fixed-site monitoring station. Linear mixed-effects models were used to examine the associations between particle exposure and anemia-related blood cell parameters, and mediation models were used to evaluate the mediation effect of TNFα on the associations. RESULTS:In the elderly participants, exposure to all measured pollutants were significantly associated with differences in anemia-related blood cell parameters, such as the association between HGB difference and per interquartile range (IQR) increase in average Acc concentration 14 d before clinical visits was -2.2% (95% CI: -3.8%, -0.6%). The significant associations of UFPs and Acc exposure with difference in anemia-related blood cells kept robust after adjustment for other pollutants. In advanced analysis, 25.2 % (95% CI: 7.4 %, 64.8 %) of difference in MCHC associated with average UFPs concentration 14 d before clinical visits were mediated by the level of TNFα. CONCLUSIONS:Short-term exposure to fine particles, especially UFPs and Acc, contributed to damage of anemia-related blood cell in the elderly, and systemic inflammation is a potential internal mediator. KEYWORDS: anemia-related blood cell parameters, ambient fine particles, mean corpuscular hemoglobin concentration (MCHC), tumor necrosis factor α (TNF α), ultrafine particles (UFPs), accumulated-mode particles (Acc)

Solid State Gas Sensor Systems: Deployment for an Extensive Air Quality Monitoring in Urban Environment

Introduction Air pollution is a global threat having huge impact on human health and ecosystems [1]. In urban areas, the air quality can be considered as resulting from the overlapping of three different pollution components: regional background, urban background and hot spot events. Therefore, the continuous monitoring of these components is of critical importance. Indeed, the ability to separate the three components is the key to define reduction actions of atmospheric pollution linked to the related sources and for this reason, really effective.This work demonstrates that it is possible to determine, with reliability, sensitivity and selectivity comparable to those of the analytical instruments, the pollutants’ concentration in the atmosphere using specific advanced thick film gas sensors. They are based on nanostructured metal oxides (MOX sensors) which modify their surface properties when interacting with reducing or oxidizing gases [2].Nowadays, monitoring is usually performed in few fixed stations and through mobile stations (where the conventional equipment is installed on vehicles) for temporary measurement campaigns or occasional environmental impact estimations. The equipment used in these stations is often complex, expensive and difficult to deploy, requiring controlled environmental conditions and frequent maintenance and calibrations [1].Differently, systems based on MOX gas sensors constitute an advantageous solution because of their low-cost fabrication, maintenance, and installation, low power consumption, small dimensions and of easy deployment for a wide range of situations for example along heavy traffic roads, or in historic centers where fixed monitoring stations cannot be used due to their large size. Experimental The thick film gas sensors were fabricated through screen-printing technology. The sensing layers are based on specific functional materials synthesized in form of crystalline nanometric powders via wet chemistry processes [2]. A careful coordination of all different processes involved in the gas sensors realization, such as functional material preparation, deposition of sensing layers, substrates and electronics were done to optimize the sensors’ precision and accuracy.The arrays of thick film gas sensors were assembled in small remotely controlled units and used for on-site tests. A monitoring unit (see figure A) consists in a small box to lodge the sensors, the electronic circuitry related to each sensor and a main electronic control unit provided with serial connection through which the data are transferred to a GSM module which sends them to an input data server, on request.With the aim to validate the values of gas concentrations obtained through the array of MOX sensors, few monitoring units have been exposed to the real atmosphere beside fixed-site monitoring stations for air quality control. The sensor responses were studied in comparison with the pollutant concentrations as measured by the analytical instruments. In particular, IR and UV spectrophotometers for carbon monoxide and ozone, chemiluminescence analyzer for NOx and gas chromatograph for BTEX. Results and Conclusions The developed monitoring units based on different advanced thick film gas sensors have been successfully prepared with optimal level of reliability, stability, reproducibility and used to detect gaseous pollutants in the atmosphere with the same trend observed by the conventional analytical techniques for long monitoring periods, in different seasons and areas.As example, a laboratory experiment devoted to test the stability and repeatability of sensors is reported in the figure B. In the image, the figure B refers to the alternate signal of two sensors, nominally identical, to 0.1 and 0.8 ppm of benzene. The responses, defined as ratio between the conductance in presence of benzene and the conductance in air, were 1.2 to 0.1 ppm and 2.1 to 0.8 ppm of benzene for both sensors. A second experiment is shown in figure C: the ozone concentration measured in real atmosphere through a WO3 sensor was compared with the measurements carried out by means of a conventional analyzer (UV spectrophotometer). The data are expressed in both cases as hourly average obtaining a quite good agreement. The graph is relating to one month of monitoring, while, in the inset, a zoom on few days is shown.The innovative system, based on a specific MOX sensors array, is able to detect and quantify atmospheric pollutants constituting an advantageous solution for a wide range of situations, as for example along the roads of city centers or along heavy traffic roads, or in historic centers where fixed monitoring stations cannot be used due to their large size.

Short-Term Exposure to Ambient Air Pollution and Increased Emergency Room Visits for Skin Diseases in Beijing, China.

Skin diseases have become a global concern. This study aims to evaluate the associations between ambient air pollution and emergency room visits for skin diseases under the background of improving air quality in China. Based on 45,094 cases from a general hospital and fixed-site monitoring environmental data from 2014–2019 in Beijing, China, this study used generalized additive models with quasi-Poisson regression to estimate the exposure–health associations at lag 0–1 to lag 0–7. PM2.5 and NO2 exposure were associated with increased emergency room visits for total skin diseases (ICD10: L00-L99). Positive associations of PM2.5, PM10, O3 and NO2 with dermatitis/eczema (ICD-10: L20–30), as well as SO2 and NO2 with urticaria (ICD-10: L50) visits were also found. For instance, a 10 μg/m3 increase in PM2.5 was associated with increases of 0.7% (95%CI: 0.2%, 1.2%) in total skin diseases visits at lag 0–5 and 1.1% (95%CI: 0.6%, 1.7%) in dermatitis/eczema visits at lag 0–1, respectively. For PM2.5, PM10 and CO, stronger annual associations were typically observed in the high-pollution (2014) and low-pollution (2018/2019) years. For instance, a 10 μg/m3 increase in PM2.5 at lag 0–5 was associated with increases of 1.8% (95%CI: 1.0%, 2.6%) and 2.3% (95%CI: 0.4%, 4.3%) in total skin disease visits in 2014 and 2018, respectively. Our study emphasizes the necessity of controlling the potential health hazard of air pollutants on skin, although significant achievements in air quality control have been made in China.