Health damage assessment of reconstruction dust from old industrial buildings under multi-process

The regeneration of old industrial buildings produces considerable construction dust, thereby seriously threatening the occupational health of construction workers. The existing articles concerning the exposure and health impacts of reconstruction dust in enclosed spaces are limited, but this research field has received increasing attention. In this study, multi-process during the demolition and reinforcement stages of a reconstruction project were monitored to determine the respirable dust concentration distribution. A questionnaire survey was conducted to obtain the exposure parameters of reconstruction workers. Moreover, a health damage assessment system for the reconstruction process of old industrial buildings was established by applying the disability-adjusted life year and human capital method to explore the health damage caused by the generated dust at different stages to the construction personnel. The assessment system was applied to the reconstruction stage of an old industrial building regeneration project in Beijing to obtain dust health damage values for different work types and to conduct comparative analysis. The results indicate that there are significant differences in the dust concentration and health damage at different stages. During the demolition stage, the manual demolition of concrete structures has the highest dust concentration, reaching 0.96 mg/m³. This exceeds the acceptable concentration by 37%, and the health damage cost is 0.58 yuan per person per day. In the reinforcement stage, the dust concentration generated by mortar/concrete mixing is the highest, but the risk level is acceptable. The health damage cost of concrete grinding, which is 0.98 yuan per person per day, is the highest. Therefore, it is necessary to strengthen the protective facilities and improve the reconstruction technology to reduce dust pollution. The results of this study can help in improving the existing dust pollution control measures at construction sites to reduce the risk of dust hazards during reconstruction.

Remote sensing identification of green plastic cover in urban built-up areas

Urban renewal can transform areas that are not adapted to modern urban life, allowing them to redevelop and flourish; however, the renewal process generates many new construction sites, producing environmentally harmful construction dust. The widespread use of urban green plastic cover (GPC) at construction sites and the development of high-resolution satellites have made it possible to extract the spatial distribution of construction sites and provide a basis for environmental protection authorities to protect against dust sources. Existing GPC extraction methods based on remote sensing images are either difficult to obtain the exact boundary of GPC or cannot provide corresponding algorithms according to different application scenarios. In order to determine the distribution of green plastic cover in the built-up area, this paper selects a variety of typical machine learning algorithms to classify the land cover of the test area image and selects K-nearest neighbor as the best machine learning algorithm through accuracy evaluation. Then multiple deep learning methods were used and the top networks with high overall scores were selected by comparing various aspects. Then these networks were used to predict the GPC of the test area image, and the accuracy evaluation results showed that the segmentation accuracy of deep learning was much higher than that of machine learning methods, but it took more time to predict. Therefore, combining different application scenarios, this paper gives the corresponding suggested methods for GPC extraction.

Exposure to construction dust and health impacts - A review

Construction dust contributes a significant proportion of airborne particulate matter, affecting the health of its surrounding environment and population. Construction workers are normally exposed to dust at high levels and bear severe health risks. The existing articles concerning the exposure and health impacts of construction dust are limited, but this research field has received more and more attention. This work reviews literature in the field and tries to systematically assess the current research state. Here, we review (1) methods used to monitor or sample construction dust; (2) main characteristics of construction dust, including dust classification, exposed populations, and exposure concentrations; (3) potential health hazards and (4) health risk assessment of construction dust. From existing literature, the exposure concentrations of different types and sources of construction dust are usually the focus of attention, while its particle size distribution and chemical composition are rarely mentioned. The classification and characteristics of populations exposed to construction dust ought to be a key consideration but not clear enough so far. There still lacks in-depth study of health hazards and systematic assessment of risks associated with construction dust. In future, it is valuable to develop utility instruments to precisely monitor construction dust. Besides, control means to reduce the pollution of construction dust deserve more studies. Health hazards of construction dust should be verified by biological experiments. Moreover, emerging algorithm models should be utilized in the risk assessment. The findings will help gain a better understanding of construction dust exposure and associated health risks.

A review on health risk assessment of PM in the construction industry - Current situation and future directions

Particulate matter (PM) is one of the primary pollutants of the environment. The amount of PM discharged from construction projects is considerably high; it generates 70-80% of the overall PM. The composition of PM is complex and may contain various toxic substances that have severe health effects on human health. Existing health risk assessment in the construction industry lacks the efficiency to reduce the risk level of PM exposure. This study systematically reviews literature in this research area to understand the primary reasons which generates PM health risk assessments. The authors reviewed health risk assessment studies in the construction industry to analyze the current situation, and then reviewed health risk assessment studies from four different industries to compare the advancement of research and outcomes in all the five industries. From the study it is understood that the area of research related to ambient air were more developed compared to those in other areas due to their sampling methods and the size of the PM studied. From the findings of the systematic review, it is understood that majority of the risk assessment studies still rely on a two decade-old system and neglect recent research findings pertaining inhalation rate and size of PM. To overcome this, the level of risk involved in various common construction activities needs to be explored using real-time location-based PM monitoring and real-time inhalation monitoring methods. The findings of this review will help researchers gain a better perspective while conducting occupational health risk studies in the construction industry.

Data on different sized particulate matter concentration produced from a construction activity

Particulate matter (PM) exposure is produced during most of the construction activities. The dataset was acquired from an experimental investigation by monitoring PM10, PM2.5, and PM1 concentration produced while building a solid concrete block wall. Alphasense OPC-N2 sensors and Sharp GP2Y1010 sensors were collocated in each of the monitoring stations (MS) to measure the PM concentration. The data was collected at 2 s time interval during the entire 40 min of the activity. The data can be utilized for study PM produced and propagated from construction. Furthermore, the dataset can be used to improve the awareness of the construction professionals about the PM production and exposure during the construction works and refine the current construction practices.

Urban dust in the Guanzhong basin of China, part II: A case study of urban dust pollution using the WRF-Dust model

We developed a regional dust dynamical model (WRF-Dust) to simulate surface dust concentrations in the Guanzhong (GZ) basin of China during two typical dust cases (19th Aug. and 26th Nov., 2013), and compared model results with the surface measurements at 17 urban and rural sites. The important improvement of the model is to employ multiple high-resolution (0.5-500 m) remote sensing data to construct dust sources. The new data include the geographic information of constructions, croplands, and barrens over the GZ basin in summer and winter of 2013. For the first time, detailed construction dust emissions have been introduced in a regional dust model in large cities of China. Our results show that by including the detailed dust sources, model performance at simulating dust pollutions in the GZ basin is significantly improved. For example, the simulated dust concentration average for the 17 sites increases from 28 μg m(-3) to 59 μg m(-3), closing to the measured concentration of 66 μg m(-3). In addition, the correlation coefficient (r) between the calculated and measured dust concentrations is also improved from 0.17 to 0.57, suggesting that our model better presents the spatial variation. Further analysis shows that urban construction activities are the crucial source in controlling urban dust pollutions. It should be considered by policy makers for mitigating particulate air pollution in many Chinese cities.