Exposure to respirable dust among workers fabricating aluminium trihydroxide-containing synthetic countertops

The aim of this study is to characterize personal exposure of workers to respirable particulate matter (PM) generated in cutting and other fabrication activities when fabricating acryl polymer/aluminium trihydroxide synthetic countertops. We collected 29 personal full-day samples of respirable PM from three workers in a small private workshop. We tested differences between- and within-worker variances of mass concentrations using the Kruskall-Wallis test. We used segmented regression to test the means and medians 15-min interval concentrations changes over time and to identify a breakpoint. Respirable PM concentrations ranged nearly 100-fold, from 0.280 to 25.4 mg/m3 with a median of 2.0 mg/m3 (1-min concentrations from 13,920 data points). There were no statistical difference in daily median or geometric mean concentrations among workers, whereas the concentrations were significantly higher on days with three versus two workers present. The 15-min median concentrations (n = 974 measures) increased until 2.35 h (beta 0.177; p < 0.05), representing a 0.70 mg increase in exposure per hour. This was followed by a plateau in concentrations. The high levels of respirable PM we observed among workers fabricating aluminium trihydroxide-containing synthetic countertops highlight an unmet early prevention need.

Spatial Correlation of Air Pollution and Its Causes in Northeast China

To understand the status of air pollution in northeastern China, we explore the structure of air pollution transmission networks and propose targeted policy recommendations. Using air pollution data from 35 cities in northeastern China for a total of 879 periods from 6 January 2015 to 3 June 2017, this paper used social network analysis (SNA) to construct a spatial association network of air pollution in the region, and analyzed the spatial association of air pollution among cities and its causes in an attempt to reveal the transmission path of air pollution in the region. The results show that inter-city air pollution in northeast China forms a complex and stable correlation network with obvious seasonal differences of “high in winter and low in summer”. Different cities in the region play the roles of “spillover”, “intermediary” and “receiver” of air pollution in the network. Small respirable particulate (PM2.5) pollution constitutes a significant component of air pollution in northeast China, which spreads from Liaoning province to Heilongjiang province via Jilin province. Therefore, regional joint pollution prevention and control measures should be adopted to combat the air pollution problem, and different treatment measures should be developed for different city “roles” in the pollution network, in order to fundamentally solve the air pollution problem in the region.

Analysis of Fine Gained Air Quality Using Deep Learning

With the rapid development of industrialization and urbanization, air pollution is increasing at an alarming rate in many developing countries. The four air pollutants which are becoming a concerning threat to human health are namely respirable particulate matter, nitrogen oxides, particulate matter and sulphur dioxide. The models which are currently used for air quality prediction by comparing to the AQI indexes do not give satisfactory results, which inspired us to examine the methods of predicting air quality based on deep learning using the K-Mean Clustering algorithm and Image Processing Technique. The interpolation, prediction, and feature analysis of fine-gained air quality are three important topics in the area of air computing. A good interpolation helps to estimate the limited air quality monitoring stations whose distribution is uneven in a city; an accurate prediction provides valuable information to protect humans and take necessary measures to reduce the effect of air pollution; a reasonable feature analysis is used to provide a more effective and general model. Overall, finding solutions to these topics can bring out extremely useful information to support air pollution control, and consequently generate great societal and technical impacts.

Inhalable Particulate (PM10) Emission Externalities From Overburden Dumps and Associated Health Risk Assessment in Densely Populated Coalfield

Overburden (OB) dumps and associated haulage are the significant contributors to increased respirable particulate levels in mining areas. Earlier studies have only focused on reporting seasonal variation of size-segregated particle mass concentration, limiting the role of specific emission sources on sensitive receptors nearby. This study estimated the impact of OB dump expansion (between years 2016 to 2018) with associated haulage on spatial pattern of particulate concentration, associated health effects, and health cost. Furthermore, a model to identify critical health risk zones was also developed. Haulage of OB and its unloading contributed to a significant increase in particulate concentration on the windward side. Moreover, OB dumping resulted in a higher respiratory dose for workers and inhabitants nearby the OB dumpsite. The results indicated that coughing along with lower respiratory problems were the dominant health effects. Moreover, the cases of lower respiratory symptoms due to PM10 emissions from OB dumps increased in 2018. The risk potential model indicated a 4.9% increase in high risk category for population exposed to PM10 emission from OB expansion within two years. An alternative management option was proposed to reduce health risk potential. The control resulted in 73% peak concentration curtailment and 84% reduction in the surface area exceeding prescribed PM10 (100 µg/m3) levels. The said study will be useful in demarcating risk zones and findings have particular significance for dispersion of particulates emanating from OB dumps.

Elemental Characteristics of Respirable Particulate Matter in the Urban Atmosphere of Dehradun, Uttrakhand, India

To evaluate the ambient air quality of the Dehradun city, respirable particulate matter was collected using respirable dust sampler (RDS) and analysed for the heavy metal content using atomic absorption spectroscopy (AAS). The morphology of particulates were determined using scanning electron microscope (SEM) and the elemental composition was determined through SEM- energy dispersive spectroscopy (EDS). Particulate matter mass concentration ranged from 65.00 µg m-3 to 337.33 µg m-3. Quantified heavy metals in particulate matter were Copper (Cu), Zinc (Zn), Cobalt (Co), Manganese (Mn), Iron (Fe), Nickel (Ni), Chromium (Cr), Lead (Pb) and Cadmium (Cd). The order of concentration of heavy metals were found to be in the trend of Fe>Zn>Cu>Pb>Cr>Ni>Mn>Co>Cd. Maximum concentration of PM10 was found at commercial site during summer, winter and monsoon season. Enrichment factor analysis showed substantial contribution of anthropogenic activities on PM10. Source apportionment (varimax rotated factor analysis method) showed dominance of incineration and uncontrolled burning of waste and refuses, resuspended dust with vehicular emission and crustal sources as the dominant sources in Dehradun. Plantation drive strategy have major role in ambient particulate matter mitigation measures and carbon sequestration from climate change and global problem worldwide. This study will be help to mitigate or decrease the load of air pollution by the using of various trees for sustainable human development on the marvellous earth planet.

Health Risk Analysis of Elemental Components of an Industrially Emitted Respirable Particulate Matter in an Urban Area

Particulate matter of aerodynamic diameter of less than 2.5 µm (PM2.5) is a recognised carcinogen and a priority air pollutant owing to its respirable and toxic chemical components. There is a dearth of information in South Africa on cancer and non-cancer risks of exposure to heavy metal (HM) content of PM2.5. This study determined the seasonal concentration of HM in PM2.5 and the cancer and non-cancer risks of exposure to HM in PM2.5. Ambient PM2.5 was monitored and samples were collected during the winter and summer months in an industrialized area in South Africa. Concentration levels of nine HMs—As, Cu, Cd, Cr, Fe, Mn, Ni, Pb, and Zn—were determined in the PM2.5 samples using inductive coupled optical emission spectrophotometry. The non-cancer and cancer risks of each metal through the inhalation, ingestion and dermal routes were estimated using the Hazard Quotient and Excess Lifetime Cancer Risk (ELCR), respectively, among infants, children, and adults. Mean concentration of each HM-bound PM2.5 was higher in winter than in summer. The probability of the HM to induce non-cancer effects was higher during winter than in summer. The mean ELCR for HMs in PM2.5 (5.24 × 10−2) was higher than the acceptable limit of 10−6 to 10−4. The carcinogenic risk from As, Cd, Cr, Ni, and Pb were higher than the acceptable limit for all age groups. The risk levels for the carcinogenic HMs followed the order: Cr > As > Cd > Ni > Pb. The findings indicated that the concentrations of HM in PM2.5 demonstrated a season-dependent pattern and could trigger cancer and non-cancer health risks. The formulation of a regulatory standard for HM in South Africa and its enforcement will help in reducing human exposure to HM-bound PM2.5.

The Effects of Virgin and Recycled PA12 Powders in SLS Processes on Occupational Exposures

Particulate matter and ultrafine particles are emitted during the pre-processing and post-processing activities of selective laser sintering (SLS) processes, which is major concern to operators exposed to the powders. This study aims to determine the occupational exposure (in terms of the total particle concentration and respirable particulate concentration) during the pre-processing and post-processing activities of SLS processes using virgin and recycled polyamide 12 (PA12) powders. Personal air sampling was performed for each activity according to the NIOSH 0500 and NIOSH 0600 methods. Based on the results, both powders were uniform spheres with a particle size of 40–60 μm. The total particulate concentration was most significant during the following pre-processing activities: 1) pouring powder into the mixing machine and 2) transferring the powder to the SLS AM machine. The total particulate concentration and respirable particulate concentration were slightly higher for the virgin powder for these activities. In conclusion, the virgin and recycled PA12 powders were both inhalable and respirable, which poses serious health hazards to the SLS AM operators. Hence, it is essential for operators to use suitable personal protective equipment (including respirators) and the working practices need to be improved by automating

Evaluation of Low-Cost Optical Particle Counters for Agricultural Exposure Measurements

HighlightsThe OPC-N3, developed by Alphasense, may be useful in measuring occupational exposure in agricultural settings based on the agreement with mass concentrations measured by gravimetrical filter analysis.The AirBeam2 is better suited for environmental exposure measurements rather than occupational measurements.Particle sizing by the GRIMM Mini-WRAS 1371 and the OPC-N3 show many aerosols that agricultural workers are exposed to follow a bimodal curve and are above 0.1 µm, thereby the respirator used as personal protective equipment is effective in filtering out aerosols in this occupation.Abstract. Prolonged exposure to dust has been shown to have adverse health effects in agricultural workers, primarily with the development of respiratory diseases. Low-cost sensors may be cost-effective tools for farmers to determine when they are exposed to harmful levels of dust during their workday. The purpose of this study was to identify low-cost sensors that may be reliably used in occupational settings to help workers and employers identify respirable particle matter exposure. The study utilized two different low-cost optical particle counters (OPCs) to collect data on dust exposure, which were worn on a belt by the participant: the OPC-N3 developed by Alphasense and the AirBeam2 developed by HabitatMap. Additionally, an AirChek TOUCH air sampling pump fit with a respirable dust aluminum cyclone allowed for the collection of respirable particulate matter (PM4) to determine the true concentration of exposure. Results show that the PM4 measurements made by the OPC-N3 are similar to the gravimetrical filter measurement at concentrations of &lt; 50 µg/m3. In addition, the data analysis suggests that the AirBeam2 may be significantly underestimating the amount of particulate matter that farmworkers are exposed to and therefore may not be suitable for occupational exposure measurements compared to the OPC-N3. Keywords: Aerosols, Agriculture, AirBeam2, Dust, Exposure, Low-cost, Occupational, Optical particle counter, OPC-N3.

California’s COVID-19 economic shutdown reveals the fingerprint of systemic environmental racism

Racial and ethnic minorities in the United States often experience higher-than-average exposures to air pollution. However, the relative contribution of embedded institutional biases to these disparities can be difficult to disentangle from physical environmental drivers, socioeconomic status, and cultural or other factors that are correlated with exposures under status quo conditions. Over the spring and summer of 2020, rapid and sweeping COVID-19 shelter-in-place orders around the world created large perturbations to local and regional economic activity that resulted in observable changes in air pollution concentrations, compositions, and distributions. Here, we use the pandemic-related emergency order and subsequent economic slowdown to causally estimate pollution exposure disparities in California. Using both public ground-based sensor data and a citizen-science network of monitors for respirable particulate matter (PM2.5), along with satellite records of nitrogen dioxide (NO2), we show that the initial sheltering-in-place period produced disproportionate air pollution reduction benefits for Asian, Hispanic/Latinx, and low- income communities. By linking these pollution data with weather, geographic, socioeconomic, and mobility data in difference-in-differences models, we demonstrate that these disparate pollution reductions cannot be explained by environmental conditions, geography, income, or local economic activity and are instead driven by non-local activity. This study thus provides causally-identified evidence of systemic racial and ethnic bias in pollution control under business-as-usual conditions.

Case Study of In-Cab Pollutants for Nonroad Construction Equipment

Like buildings, nonroad construction equipment with enclosed cabs have doors and windows, and heating, ventilating, and air conditioning systems; thus, these machines have their own indoor air quality (IAQ) environment. Understanding the role of thermal comfort and air pollutants can help equipment operators manage in-cab environments to reduce health concerns and increase productivity. The objective of this case study was to collect and analyze IAQ data from the cabs of nonroad equipment as it performed real-world activities. Using state-of-the-art IAQ instrumentation, data were collected for in-cab pollutant concentration levels including carbon monoxide, carbon dioxide, and respirable particulate matter. Concentrations of carbon monoxide did not exceed published exposure limits for IAQ, but they did approach the published limits. Concentrations of CO2 frequently exceeded IAQ recommended levels for adequate ventilation. Concentrations of respirable particulate matter frequently exceeded IAQ recommended levels. The case study yielded enough information to conclude that studying IAQ in nonroad equipment cabs is necessary to improve human health, safety, and productivity for equipment operators.