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Aimed at evaluating the impacts of coal-fired power plants on urban air quality and human health, a one-month intensive observation campaign was conducted in a typical polluted city located in the 2 + 26 city cluster (Beijing, Tianjin and 26 other cities) of the North China Plain in December 2017. The observation results illustrated that the coal-fired power plant in this city increased the monthly average fine particulate matter (PM2.5) concentration by ~5% at the city scale. The impacts differed under various diffusion conditions. A three-dimensional nested air quality condition model (the Nested Air Quality Perdition Model System or NAQPMS) with source apportionment was employed to analyze the impacts. The results indicated that power plants had the largest effect on regional air quality during the severe-pollution period, while any influence could be ignored during periods with excellent dissipation under robust winds. PM2.5 contributed by the power plant mainly occurred below 150 m, diffused 100 km away, and reached a level of approximately 5 μg m-3 during the light-pollution period. During the accumulation period, the plume reached a height of 500 m, diffused to the downwind area approximately 100 km away within half a day, and contributed at most 40 μg m-3 to PM2.5. The affected area expanded to 250 km during the severe-pollution period, and the contribution to PM2.5 was at least 10 μg m-3 at different distances. The affected height reached approximately 500 m, with PM2.5 exceeding 10 μg m-3, mainly constrained below 150 m. Overall, regional integrated control strategies should be implemented for the power plants in the 2 + 26 city cluster during pollution episodes to further improve air quality.The use of low-cost sensor technology to monitor air pollution has made remarkable strides in the last decade. The development of low-cost devices to monitor air quality in indoor environments can be used to understand the behaviour of indoor air pollutants and potentially impact on the reduction of related health impacts. These user-friendly devices are portable, require low-maintenance, and can enable near real-time, continuous monitoring. They can also contribute to citizen science projects and community-driven science. However, low-cost sensors have often been associated with design compromises that hamper data reliability. Moreover, with the rapidly increasing number of studies, projects, and grey literature based on low-cost sensors, information got scattered. Intending to identify and review scientifically validated literature on this topic, this study critically summarizes the recent research pertinent to the development of indoor air quality monitoring devices using low-cost sensors. The method employed for this review was a thorough search of three scientific databases, namely ScienceDirect, IEEE, and Scopus. A total of 891 titles published since 2012 were found and scanned for relevance. Finally, 41 research articles consisting of 35 unique device development projects were reviewed with a particular emphasis on device development calibration and performance of sensors, the processor used, data storage and communication, and the availability of real-time remote access of sensor data. ONO-7475 solubility dmso The most prominent finding of the study showed a lack of studies consisting of sensor performance as only 16 out of 35 projects performed calibration/validation of sensors. An even fewer number of studies conducted these tests with a reference instrument. Hence, a need for more studies with calibration, credible validation, and standardization of sensor performance and assessment is recommended for subsequent research.Assessing the health risks associated with emerging contaminants in groundwater systems is a complex issue that has been receiving increased attention in indirect potable reuse applications. Among several emerging contaminants, our study focuses on developing a numerical model that aims to compute the transport characteristics of Bisphenol A (BPA) in a 3D spatially heterogeneous aquifer under uncertainty. Traditional approaches that characterize the health risk of BPA to humans rely on the monotonic dose-response (MDR) relationship with a regulatory dose limit. Recent public health studies indicate that BPA can cause endocrine-related health effects in specific low dose ranges, which requires the consideration of the non-monotonic dose-response (NMDR) model. This work investigates the impact of different BPA DR models (i.e., monotonic vs. non-monotonic) on the resilience of the aquifer against BPA contamination in the presence of hydrogeological heterogeneity. For the resilience estimation, a systematic stochastic methodology linking risk characterization to aquifer resilience is established. Our results show the importance of the interplay between the DR models and aquifer heterogeneity on controlling the uncertainty of the resilience loss RL (d) at a specified environmentally sensitive target. In the increased level of aquifer heterogeneity, the uncertainty bounds are higher for RL estimated through the NMDR model as opposed to the MDR model. Moreover, RL is controlled by η (-), the ratio of the volumetric flow rate at the source zone to the average flow rate at the background aquifer. In a risk management perspective, the consideration of the NMDR model needs to be emphasized due to its impact on the uncertainty of RL. A critical case is when the land use of a contamination site indicates a large number of the vulnerable population to endocrine-related health effects. In this case, η as an indicator of aquifer resilience can reduce the uncertainty of RL.The use of cars for drop-off and pick-up of pupils from schools is a potential cause of pollution hotspots at school premises. Employing a joint execution of smart sensing technology and citizen science approach, a primary school took an initiative to co-design a study with local community and researchers to generate data and provide information to understand the impact on pollution levels and identify possible mitigation measures. This study was aimed to assess the hotspots of vehicle-generated particulate matter ≤2.5 μm (PM2.5) and ≤10 μm (PM10) at defined drop-off/pick-up points and its ingress into a nearby naturally ventilated primary school classroom. Five different locations were selected inside school premises for measurements during two peak hours morning (MP; 0730-0930 h; local time), evening (EP; 1400-1600 h), and off-peak (OP; 1100-1300 h) hours for comparison. These represent PM measurements at the main road, pick-up point at the adjoining road, drop-off point, a classroom, and the school playground.