Deep learning architecture for air quality predictions

With the rapid development of urbanization and industrialization, many developing countries are suffering from heavy air pollution. Governments and citizens have expressed increasing concern regarding air pollution because it affects human health and sustainable development worldwide. Current air quality prediction methods mainly use shallow models; however, these methods produce unsatisfactory results, which inspired us to investigate methods of predicting air quality based on deep architecture models. In this paper, a novel spatiotemporal deep learning (STDL)-based air quality prediction method that inherently considers spatial and temporal correlations is proposed. A stacked autoencoder (SAE) model is used to extract inherent air quality features, and it is trained in a greedy layer-wise manner. Compared with traditional time series prediction models, our model can predict the air quality of all stations simultaneously and shows the temporal stability in all seasons. Moreover, a comparison with the spatiotemporal artificial neural network (STANN), auto regression moving average (ARMA), and support vector regression (SVR) models demonstrates that the proposed method of performing air quality predictions has a superior performance.     

The fractionation and geochemical characteristics of rare earth elements measured in ambient size-resolved PM in an integrated iron and steelmaking industry zone

Environmental Science and Pollution Research - Improved understanding of the fractionation and geochemical characteristic of rare earth elements (REEs) from steel plant emissions is important due...     

Modeling urban solar energy with high spatiotemporal resolution: A case study in Toronto,Canada

This research presents a method to determine the maximum potential for the capturing of solar radiation on the rooftop of buildings in an urban environment. This involves the modeling of solar energy potential and comparison to historical building energy demand profiles through the use of 3-D solar simulation software tools and geographic information systems (GIS). The objective is to accurately identify the amount of surface area that is suitable for solar photovoltaic (PV) installations and to estimate the hourly PV electricity generation potential of existing building rooftops in an urban environment. This study demonstrates a viable approach for modeling urban solar energy and offers valuable information for electricity distributors, policy makers, and urban energy planners to facilitate the substantial design of a green built environment. The developed methodology is comprised of three main sections: (1) determination of suitable rooftop area, (2) determination of the amount of incident solar radiation available per rooftop, and (3) estimation of hourly solar PV electricity generation potential. A case study was performed using this method for Ryerson University, located in Toronto, Canada. It was found that solar PV could supply up to 19% of the study area’s electricity demands during peak consumption hours. The potential benefits of solar PV was also estimated based upon hourly greenhouse gas emission intensity factors as well as Time-of-Use (TOU) savings through the Ontario Feed-in-Tariff (FIT) program, which allows for better representation of the positive impacts of solar technologies.     

PACE2016中国环境治理国际研讨会综述

PACE2016中国环境治理国际研讨会就中国环境政府治理、环境市场治理、环境社会治理以及环境治理结构展开了深入研讨并达成以下共识:大国模式下的环境政府治理面临着突出的"污染避难所效应"、"公平与效率的两难"和"多层次治理体系"等问题;不成熟市场经济条件下环境市场治理必然面临"要不要走环境治理市场化之路"的疑虑,相关研究表明市场手段作为有效的环境治理方式正在逐渐地打消此等疑虑;中国环境治理最主要的短板在于社会治理,提高公众参与度的主要挑战在于改变地方政府的态度,然而社会企业家是环境社会治理的希望;多元环境治理结构是中国环境治理的必然选择,政府引领、企业自觉、公众参与的制衡机制是关键。     

Regulatory effects of dioxin-like and non-dioxin-like PCBs and other AhR ligands on the antioxidant enzymes paraoxonase 1/2/3

Paraoxonase 1 (PON1), an antioxidant enzyme, is believed to play a critical role in many diseases, including cancer. PCBs are widespread environmental contaminants known to induce oxidative stress and cancer and to produce changes in gene expression of various pro-oxidant and antioxidant enzymes. Thus, it appeared of interest to explore whether PCBs may modulate the activity and/or gene expression of PON1 as well. In this study, we compared the effects of dioxin-like and non-dioxin-like PCBs and of various aryl hydrocarbon receptor (AhR) ligands on PON1 regulation and activity in male and female Sprague-Dawley rats. Our results demonstrate that (i) the non-dioxin-like PCB154, PCB155, and PCB184 significantly reduced liver and serum PON1 activities, but only in male rats; (ii) the non-dioxin-like PCB153, the most abundant PCB in many matrices, did not affect PON1 messenger RNA (mRNA) level in the liver but significantly decreased serum PON1 activity in male rats; (iii) PCB126, an AhR ligand and dioxin-like PCB, increased both PON1 activities and gene expression; and (iv) even though three tested AhR ligands induced CYP1A in several tissues to a similar extent, they displayed differential effects on the three PONs and AhR, i.e., PCB126 was an efficacious inducer of PON1, PON2, PON3, and AhR in the liver, while 3-methylcholantrene induced liver AhR and lung PON3, and 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), the most potent AhR agonist, increased only PON3 in the lung, at the doses and exposure times used in these studies. These results show that PCBs may have an effect on the antioxidant protection by paraoxonases in exposed populations and that regulation of gene expression through AhR is highly diverse.     

Trends and variations of pH and hardness in a typical semi-arid river in a monsoon climate region during 1985–2009

The rapid growth of urbanization and industrialization, along with dramatic climate change, has strongly influenced hydrochemical characteristics in recent decades in China and thus could cause the variation of pH and general total hardness of a river. To explore such variations and their potential influencing factors in a river of the monsoon climate region, we analyzed a long-term monitoring dataset of pH, SO₄ ^2?, NO_x, general total hardness (GH), Mg²⁺, Ca²⁺, and Cl^? in surface water and groundwater in the Luan River basin from 1985 to 2009. The nonparametric Seasonal Kendall trend test was used to test the long-term trends of pH and GH. Relationship between the affecting factors, pH and GH were discussed. Results showed that pH showed a decreasing trend and that GH had an increasing trend in the long-term. Seasonal variation of pH and GH was mainly due to the typical monsoon climate. Results of correlation analysis showed that the unit area usage amounts of chemical fertilizer, NO₃ ^?, and SO₄ ^2? were negatively correlated with pH in groundwater. In addition, mining activity affected GH spatial variation. Acid deposition, drought, and increasing the use of chemical fertilizers would contribute to the acidification trend, and mining activities would affect the spatial variation of GH. Variations of precipitation and runoff in semi-arid monsoon climate areas had significant influences on the pH and GH. Our findings implied that human activities played a critical role in river acidification in the semi-arid monsoon climate region of northern China.     

Influence of Al-oxide on pesticide sorption to woody biochars with different surface areas

Biochars’ properties will change after application in soil due to the interactions with soil constituents, which would then impact the performance of biochars as soil amendment. For a better understanding on these interactions, two woody biochars of different surface areas (SA) were physically treated with aluminum oxide (Al-oxide) to investigate its potential influence on biochars’ sorption property. Both the micropore area and mesopore (17～500 Å in diameter) area of the low-SA biochar were enhanced by at least 1.5 times after treatment with Al-oxide, whereas the same treatment did not change the surface characteristics of the high-SA biochar due partly to its well-developed porosity. The enhanced sorption of the pesticide isoproturon to the Al-oxide-treated low-SA biochar was observed and is positively related to the increased mesopore area. The desorption hysteresis of pesticide from the low-SA biochar was strengthened because of more pesticide molecules entrapped in the expanded pores by Al-oxide. However, no obvious change of pesticide sorption to the high-SA biochar after Al-oxide treatment was observed, corresponding to its unchanged porosity. The results suggest that the influence of Al-oxide on the biochars’ sorption property is dependent on their porosity. This study will provide valuable information on the use of biochars for reducing the bioavailability of pesticides.     

Effect of alginate on the aggregation kinetics of copper oxide nanoparticles (CuO NPs): bridging interaction and hetero-aggregation induced by Ca<Superscript>2+</Superscript>

The stability of CuO nanoparticles (NPs) is expected to play a key role in the environmental risk assessment of nanotoxicity in aquatic systems. In this study, the effect of alginate (model polysaccharides) on the stability of CuO NPs in various environmentally relevant ionic strength conditions was investigated by using time-resolved dynamic light scattering. Significant aggregation of CuO NPs was observed in the presence of both monovalent and divalent cations. The critical coagulation concentrations (CCC) were 54.5 and 2.9 mM for NaNO₃ and Ca(NO₃)₂, respectively. The presence of alginate slowed nano-CuO aggregation rates over the entire NaNO₃ concentration range due to the combined electrostatic and steric effect. High concentrations of Ca²⁺ (>6 mM) resulted in stronger adsorption of alginate onto CuO NPs; however, enhanced aggregation of CuO NPs occurred simultaneously under the same conditions. Spectroscopic analysis revealed that the bridging interaction of alginate with Ca²⁺ might be an important mechanism for the enhanced aggregation. Furthermore, significant coagulation of the alginate molecules was observed in solutions of high Ca²⁺ concentrations, indicating a hetero-aggregation mechanism between the alginate-covered CuO NPs and the unabsorbed alginate. These results suggested a different aggregation mechanism of NPs might co-exist in aqueous systems enriched with natural organic matter, which should be taken into consideration in future studies.

Open image in new window

Graphical abstract Hetero-aggregation mechanism of CuO nanoparticles and alginate under high concentration of Ca²⁺

     

Deodorization of pig manure using lignin peroxidase with different electron acceptors

Odor pollution is a big environmental problem caused by large-scale livestock production in China, and developing a practical way to reduce these odors is pressing. In this study, a combination of 0.2–1.0 U/mL lignin peroxidase (LiP) and one of three peroxides (H₂O₂, CaO₂, 2Na₃CO₃·3H₂O₂) was examined for its efficiency in reducing the release of eight chemicals (propionic acid, isobutyric acid, isocaproic acid, isovaleric acid, phenol, p-cresol, indole, and skatole), NH₃, H₂S, and odor intensity from pig manure. The results showed an approximately 90% reduction in p-cresol, 40–60% reduction in odor intensity, 16.5–40% reduction in indolic compounds, and 25–40% reduction in volatile fatty acids. Being the electron acceptors of LiP, 2Na₃CO₃·3H₂O₂ and CaO₂ performed better than H₂O₂ in reducing the concentration of eight chemicals, NH_3, H₂S, and odor intensity from pig manure. The effect of deodorization can last for up to 72 hr.

Implications: In China, one of the major environmental problems caused by confined feeding is odor pollution, which brings a major threat to the sustainability, profitability, and growth of the livestock industry. To couple the LiP with the electron acceptors, a low–cost, simple, and feasible method for odor removal was established in this study. Based on the study results, a practical treatment method was provided for odor pollution and supply the farm operators a more flexible time to dispose treated manure.     

Vehicle emission implications of drivers’ smart advisory system for traffic operations in work zones

Wireless communication systems have been broadly applied in various complicated traffic operations to improve mobility and safety on roads, which may raise a concern about the implication of the new technology on vehicle emissions. This paper explores how the wireless communication systems improve drivers’ driving behaviors and its contributions to the emission reduction, in terms of Operating Mode (OpMode) IDs distribution used in emission estimation. A simulated work zone with completed traffic operation was selected as a test bed. Sixty subjects were recruited for the tests, whose demographic distribution was based on the Census data in Houston, Texas. A scene of a pedestrian’s crossing in the work zone was designed for the driving test. Meanwhile, a wireless communication system called Drivers Smart Advisory System (DSAS) was proposed and introduced in the driving simulation, which provided drivers with warning messages in the work zone. Two scenarios were designed for a leading vehicle as well as for a following vehicle driving through the work zone, which included a base test without any wireless communication systems, and a driving test with the trigger of the DSAS. Subjects’ driving behaviors in the simulation were recorded to evaluate safety and estimate the vehicle emission using the Environmental Protection Agency (EPA) released emission model MOVES. The correlation between drivers’ driving behavior and the distribution of the OpMode ID during each scenario was investigated. Results show that the DSAS was able to induce drivers to accelerate smoothly, keep longer headway distance and stop earlier for a hazardous situation in the work zone, which driving behaviors result in statistically significant reduction in vehicle emissions for almost all studied air pollutants (p-values range from 4.10E-51 to 2.18E-03). The emission reduction was achieved by the switching the distribution of the OpMode IDs from higher emission zones to lower emission zones.

Implications: Transportation section is a significant source of greenhouse gas emissions. Many studies demonstrate that the wireless communication system dedicated for safety and mobility issues may contribute to the induction in vehicle emissions through changing driving behaviors. An insight into the correlation between the driving behaviors and the distribution of Operating Mode (OpMode) IDs is essential to enhance the emission reduction. The result of this study shows that with a Drivers Smart Advisory System (DSAS) drivers accelerated smoothly and stopped earlier for a hazardous situation, which induce the switch of the OpMode IDs from high emission zones to lower emission zones.