A comparison of PM exposure related to emission hotspots in a hot and humid urban environment: Concentrations, compositions, respiratory deposition, and potential health risks

Particle number concentration, particle size distribution, and size-dependent chemical compositions were measured at a bus stop, alongside a high way, and at an industrial site in a tropical city. It was found that the industry case had 4.93 × 107–7.23 × 107 and 3.44 × 104–3.69 × 104 #/m3 higher concentration of particles than the bus stop and highway cases in the range of 0.25–0.65 μm and 2.5–32 μm, respectively, while the highway case had 6.01 × 105 and 1.86 × 103 #/m3 higher concentration of particles than the bus stop case in the range of 0.5–1.0 μm and 5.0–32 μm, respectively. Al, Fe, Na, and Zn were the most abundant particulate inorganic elements for the traffic-related cases, while Zn, Mn, Fe, and Pb were abundant for the industry case. Existing respiratory deposition models were employed to analyze particle and element deposition distributions in the human respiratory system with respect to some potential exposure scenarios related to bus stop, highway, and industry, respectively. It was shown that particles of 0–0.25 μm and 2.5–10.0 μm accounted for around 74%, 74%, and 70% of the particles penetrating into the lung region, respectively. The respiratory deposition rates of Cr and Ni were 170 and 220 ng/day, and 55 and 140 ng/day for the highway and industry scenarios, respectively. Health risk assessment was conducted following the US EPA supplemented guidance to estimate the risk of inhalation exposure to the selected elements (i.e. Cr, Mn, Ni, Pb, Se, and Zn) for the three scenarios. It was suggested that Cr poses a potential carcinogenic risk with the excess lifetime cancer risk (ELCR) of 2.1–98 × 10− 5 for the scenarios. Mn poses a potential non-carcinogenic risk in the industry scenario with the hazard quotient (HQ) of 0.98. Both Ni and Mn may pose potential non-carcinogenic risk for people who are involved with all the three exposure scenarios

Comparison of the co-gasification of sewage sludge and food wastes and cost-benefit analysis of gasification- and incineration-based waste treatment schemes

The compositions of food wastes and their co-gasification producer gas were compared with the existing data of sewage sludge. Results showed that food wastes are more favorable than sewage sludge for co-gasification based on residue generation and energy output. Two decentralized gasification-based schemes were proposed to dispose of the sewage sludge and food wastes in Singapore. Monte Carlo simulation-based cost-benefit analysis was conducted to compare the proposed schemes with the existing incineration-based scheme. It was found that the gasification-based schemes are financially superior to the incineration-based scheme based on the data of net present value (NPV), benefit-cost ratio (BCR), and internal rate of return (IRR). Sensitivity analysis was conducted to suggest effective measures to improve the economics of the schemes

Variation of household electricity consumption and potential impact of outdoor PM2.5 concentration: a comparison between Singapore and Shanghai

The auto-regressive distributed lag (ARDL) bound testing approach was used to study the relationships between the monthly household electricity consumption and outdoor PM2.5 concentration with the consideration of ambient temperature and the number of rainy days for Singapore and Shanghai. It is shown that there are significant long-run relationships between the household electricity consumption and the regressors for both Singapore and Shanghai. For Singapore, a 20% increase in the PM2.5 concentration of a single month is in the long-run significantly related to a 0.8% increase in the household electricity consumption. This corresponds to an electricity overconsumption of 5.0 GWh, a total of 0.7–1.0 million USD in electricity cost, and 2.1 kilotons of CO2 emission associated with electricity generation. For Shanghai, a 20% decrease in the PM2.5 concentration of a single month is in the long-run significantly related to a 2.2% decrease in the household electricity consumption. This corresponds to a 35.0 GWh decrease in the overall household electricity consumption, 1.6–5.1 million USD decrease in electricity cost, and 17.5 kilotons of CO2 emission. The results suggest that the cost of electricity consumption should be included in the economic cost analysis of PM2.5 pollution in the future. A 1 °C increase in the monthly temperature is in the long-run significantly related to a 13.6% increase in the monthly electricity consumption for Singapore, while a 30 degree days increase in heating & cooling days (HCDD) is in the long-run significantly related to a 24.9% increase in the monthly electricity consumption for Shanghai. A 5-day increase in the number of rainy days per month is in the long-run significantly related to a 3.0% and 5.8% increase in the monthly electricity consumption for Singapore and Shanghai, respectively

On the association between outdoor PM 2.5 concentration and the seasonality of tuberculosis for Beijing and Hong Kong

Tuberculosis (TB) is still a serious public health problem in various countries. One of the long-elusive but critical questions about TB is what the risk factors are and how they contribute for its seasonality. An ecologic study was conducted to examine the association between the variation of outdoor PM2.5 concentration and the TB seasonality based on the monthly TB notification and PM2.5 concentration data of Hong Kong and Beijing. Both descriptive analysis and Poisson regression analysis suggested that the outdoor PM2.5 concentration could be a potential risk factor for the seasonality of TB disease. The significant relationship between the number of TB cases and PM2.5 concentration was not changed when regression models were adjusted by sunshine duration, a potential confounder. The regression analysis showed that a 10 μg/m3 increase in PM2.5 concentrations during winter is significantly associated with a 3% (i.e. 18 and 14 cases for Beijing and Hong Kong, respectively) increase in the number of TB cases notified during the coming spring or summer for both Beijing and Hong Kong. Three potential mechanisms were proposed to explain the significant relationship: (1) increased PM2.5 exposure increases host's susceptibility to TB disease by impairing or modifying the immunology of the human respiratory system; (2) increased indoor activities during high outdoor PM2.5 episodes leads to an increase in human contact and thus the risk of TB transmission; (3) the seasonal change of PM2.5 concentration is correlated with the variation of other potential risk factors of TB seasonality. Preliminary evidence from the analysis of this work favors the first mechanism about the PM2.5 exposure-induced immunity impairment. This work adds new horizons to the explanation of the TB seasonality and improves our understanding of the potential mechanisms affecting TB incidence, which benefits the prevention and control of TB disease

Particulate emission from the gasification and pyrolysis of biomass: concentration, size distributions, respiratory deposition-based control measure evaluation

Gasification and pyrolysis technologies have been widely employed to produce fuels and chemicals from solid wastes. Rare studies have been conducted to compare the particulate emissions from gasification and pyrolysis, and relevant inhalation exposure assessment is still lacking. In this work, we characterized the particles emitted from the gasification and pyrolysis experiments under different temperatures (500, 600, and 700 °C). The collection efficiencies of existing cyclones were compared based on particle respiratory deposition. Sensitivity analysis was conducted to identify the most effective design parameters. The particles emitted from both gasification and pyrolysis process are mainly in the size range 0.25–1.0 μm and 1.0–2.5 μm. Particle respiratory deposition modelling showed that most particles penetrate deeply into the last stage of the respiratory system. At the nasal breathing mode, particles with sizes ranging from 0.25 to 1.0 μm account for around 91%, 74%, 76%, 90%, 84%, and 79% of the total number of particles that deposit onto the last stage in the cases of 500 °C gasification, 600 °C gasification, 700 °C gasification, 500 °C pyrolysis, 600 °C pyrolysis, and 700 °C pyrolysis, respectively. At the oral breathing mode, particles with sizes ranging from 0.25 to 1.0 μm account for around 92%, 77%, 79%, 91%, 86%, and 81% of the total number of particles that deposit onto the last stage in the six cases, respectively. Sensitivity analysis showed that the particle removal efficiency was found to be most sensitive to the cyclone vortex finder diameter (D0). This work could potentially serve as the basis for proposing health protective measures against the particulate pollution from gasification and pyrolysis technologies

Co-gasification of woody biomass and chicken manure: Syngas production, biochar reutilization, and cost-benefit analysis

The management and disposal of livestock manure has become one of the top environmental issues at a global scale in line with the tremendous growth of poultry industry over the past decades. In this work, a potential alternative method for the disposal of chicken manure from Singapore local hen layer farms was studied. Gasification was proposed as the green technology to convert chicken manure into clean energy. Through gasification experiments in a 10 kW fixed bed downdraft gasifier, it was found that chicken manure was indeed a compatible feedstock for gasification in the presence of wood waste. The co-gasification of 30 wt% chicken manure and 70 wt% wood waste produced syngas of comparable quality to that of gasification of pure wood waste, with a syngas lower heating value (LHV) of 5.23 MJ/Nm3 and 4.68 MJ/Nm3, respectively. Furthermore, the capability of the gasification derived biochar in the removal of an emerging contaminant (artificial sweetener such as Acesulfame, Saccharin and Cyclamate) via adsorption was also conducted in the second part of this study. The results showed that the biochar was effective in the removal of the contaminant and the mechanism of adsorption of artificial sweetener by biochar was postulated to be likely via electrostatic interaction as well as specific interaction. Finally, we conducted a cost-benefit analysis for the deployment of a gasification system in a hen layer farm using a Monte Carlo simulation model

On the temporal modelling of solar photovoltaic soiling: energy and economic impacts in seven cities

This work developed a framework to predict the energy and economic impacts of solar photovoltaic soiling. This framework includes the effects of relative humidity, precipitation and tilt angle on solar photovoltaic soiling. A concept of relative net-present value change was introduced to determine the optimal cleaning interval. The uncertainties in the economic analysis were accounted for using a Monte Carlo simulation method. The framework was used to study the soiling-induced efficiency and economic losses of solar photovoltaic modules in seven cities (i.e. Taichung, Tokyo, Hami, Malibu, Sanlucar la Mayor, Doha, and Walkaway). Overall, the efficiency loss (in ascending order) for Tokyo/Walkaway < Taichung < Sanlucar la Mayor < Malibu/Hami < Doha for a one-year study period. Doha experiences an efficiency loss over 80% for a 140-day exposure, while Tokyo has an efficiency loss less than 4% for a one-year exposure. Malibu has longest optimal cleaning intervals (70 days for manual cleaning and 49 days for machine-assisted cleaning) that leads to the relative net-present value changes of 1.7% and 1.1%. Doha has the shortest optimal cleaning intervals (23 days for manual cleaning and 17 days for machine-assisted cleaning) that leads to the relative net-present value changes of 21% and 19%. The work serves as an effective tool for designing optimal cleaning protocols for solar photovoltaic systems

Paths to sustainable plastic waste recycling

No abstract available

Simple and Effective Relation-based Embedding Propagation for Knowledge Representation Learning

Relational graph neural networks have garnered particular attention to encode graph context in knowledge graphs (KGs). Although they achieved competitive performance on small KGs, how to efficiently and effectively utilize graph context for large KGs remains an open problem. To this end, we propose the Relation-based Embedding Propagation (REP) method. It is a post-processing technique to adapt pre-trained KG embeddings with graph context. As relations in KGs are directional, we model the incoming head context and the outgoing tail context separately. Accordingly, we design relational context functions with no external parameters. Besides, we use averaging to aggregate context information, making REP more computation-efficient. We theoretically prove that such designs can avoid information distortion during propagation. Extensive experiments also demonstrate that REP has significant scalability while improving or maintaining prediction quality. Notably, it averagely brings about 10% relative improvement to triplet-based embedding methods on OGBL-WikiKG2 and takes 5%-83% time to achieve comparable results as the state-of-the-art GC-OTE.Comment: Accepted by IJCAI 202