A review of polychlorinated biphenyls (PCBs) pollution in indoor air environment

Polychlorinated biphenyls (PCBs) were widely used in industrial production due to the unique physical and chemical properties. As a kind of persistent organic pollutants, the PCBs would lead to environment pollution and cause serious problems for human health. Thus, they have been banned since the 1980s due to the environment pollution in the past years. Indoor air is the most direct and important environment medium to human beings; thus, the PCBs pollution research in indoor air is important for the protection of human health. This paper introduces the industrial application and potential harm of PCBs, summarizes the sampling, extracting, and analytical methods of environment monitoring, and compares the indoor air levels of urban areas with those of industrial areas in different countries according to various reports. This paper can provide a basic summary for PCBs pollution control in the indoor air environment.

Implications: The review of PCBs pollution in indoor air in China is still limited. In this paper, we introduce the industrial application and potential harm of PCBs, summarize the sampling, extracting, and analytical methods of environment monitoring, and compare the indoor air levels of urban areas with industrial areas in different countries according to various reports.     

Validation of a new method for measuring and continuously monitoring the efficiency of industrial flares

A new method has been developed for a direct and remote measurement of industrial flare combustion efficiency (CE). The method is based on a unique hyper-spectral or multi-spectral Infrared (IR) imager which provides a high frame rate, high spectral selectivity and high spatial resolution. The method can be deployed for short-term flare studies or for permanent installation providing real-time continuous flare CE monitoring.

In addition to the measurement of CE, the method also provides a measurement for level of smoke in the flare flame regardless of day or night. The measurements of both CE and smoke level provide the flare operator with a real-time tool to achieve “incipient smoke point” and optimize flare performance.

The feasibility of this method was first demonstrated in a bench scale test. The method was recently tested on full scale flares along with extractive sampling methods to validate the method. The full scale test included three types of flares – steam assisted, air assisted, and pressure assisted. Thirty-nine test runs were performed covering a CE range of approximately 60-100%. The results from the new method showed a strong agreement with the extractive methods (r²=0.9856 and average difference in CE measurement=0.5%).

Implications: Because industrial flares are operated in the open atmosphere, direct measurement of flare combustion efficiency (CE) has been a long-standing technological challenge. Currently flare operators do not have feedback in terms of flare CE and smoke level, and it is extremely difficult for them to optimize flare performance and reduce emissions. The new method reported in this paper could provide flare operators with real-time data for CE and smoke level so that flare operations can be optimized. In light of EPA’s focus on flare emissions and its new rules to reduce emissions from flares, this policy-relevant development in flare CE monitoring is brought to the attention of both the regulating and regulated communities.     

Application of an integrated Weather Research and Forecasting (WRF)/CALPUFF modeling tool for source apportionment of atmospheric pollutants for air quality management: A case study in the urban area of Benxi,China

In this study, the authors endeavored to develop an effective framework for improving local urban air quality on meso-micro scales in cities in China that are experiencing rapid urbanization. Within this framework, the integrated Weather Research and Forecasting (WRF)/CALPUFF modeling system was applied to simulate the concentration distributions of typical pollutants (particulate matter with an aerodynamic diameter <10 μm [PM₁₀], sulfur dioxide [SO₂], and nitrogen oxides [NO_x]) in the urban area of Benxi. Statistical analyses were performed to verify the credibility of this simulation, including the meteorological fields and concentration fields. The sources were then categorized using two different classification methods (the district-based and type-based methods), and the contributions to the pollutant concentrations from each source category were computed to provide a basis for appropriate control measures. The statistical indexes showed that CALMET had sufficient ability to predict the meteorological conditions, such as the wind fields and temperatures, which provided meteorological data for the subsequent CALPUFF run. The simulated concentrations from CALPUFF showed considerable agreement with the observed values but were generally underestimated. The spatial-temporal concentration pattern revealed that the maximum concentrations tended to appear in the urban centers and during the winter. In terms of their contributions to pollutant concentrations, the districts of Xihu, Pingshan, and Mingshan all affected the urban air quality to different degrees. According to the type-based classification, which categorized the pollution sources as belonging to the Bengang Group, large point sources, small point sources, and area sources, the source apportionment showed that the Bengang Group, the large point sources, and the area sources had considerable impacts on urban air quality. Finally, combined with the industrial characteristics, detailed control measures were proposed with which local policy makers could improve the urban air quality in Benxi. In summary, the results of this study showed that this framework has credibility for effectively improving urban air quality, based on the source apportionment of atmospheric pollutants.

Implications: The authors endeavored to build up an effective framework based on the integrated WRF/CALPUFF to improve the air quality in many cities on meso-micro scales in China. Via this framework, the integrated modeling tool is accurately used to study the characteristics of meteorological fields, concentration fields, and source apportionments of pollutants in target area. The impacts of classified sources on air quality together with the industrial characteristics can provide more effective control measures for improving air quality.

Through the case study, the technical framework developed in this study, particularly the source apportionment, could provide important data and technical support for policy makers to assess air pollution on the scale of a city in China or even the world.     

Production of sludge-incorporated paver blocks for efficient waste management

Waste management plays a vital role in the reuse of industry wastes in to useful conversions. The treatment of effluents from the combined textile effluent treatment plant and hypo sludge from the paper industry results in sludge generation, which poses a huge challenge for its disposal. Therefore, an eco-friendly attempt is made to utilize them in the production of paver blocks. Paver blocks are construction units that have vast applications in street roads, walking paths, fuel stations, and so on. In this study, an innovative attempt has been made to manufacture paver blocks incorporating textile effluent treatment plant sludge and hypo sludge, to utilize them in suitable proportions. The effect of adding silica fume and polypropylene fibre in paver blocks has also been studied. Paver blocks containing sludge with different proportions were cast based on the recommendations in Indian Standards (IS) 15658, and the test results were compared with the nominal M20 grade and M30 grade paver blocks. The outcomes of the paver block combinations were studied and found to be an effective utilization of sludge with substantial cement replacement of up to 35%, resulting in effective waste management for specific industries.

Implications: Presently, paver blocks are construction units that have vast application in street roads and other constructions like walking paths, fuel stations, and so on. Also, paver blocks possess easy maintenance during breakages. Based on this application, an innovative attempt has been made to manufacture paver blocks incorporating textile effluent treatment plant sludge and hypo sludge to utilize them in suitable proportions.     

The study on biomass fraction estimate methodology of municipal solid waste incinerator in Korea

In Korea, the amount of greenhouse gases released due to waste materials was 14,800,000 t CO₂eq in 2012, which increased from 5,000,000 t CO₂eq in 2010. This included the amount released due to incineration, which has gradually increased since 2010. Incineration was found to be the biggest contributor to greenhouse gases, with 7,400,000 t CO₂eq released in 2012. Therefore, with regards to the trading of greenhouse gases emissions initiated in 2015 and the writing of the national inventory report, it is important to increase the reliability of the measurements related to the incineration of waste materials.

This research explored methods for estimating the biomass fraction at Korean MSW incinerator facilities and compared the biomass fractions obtained with the different biomass fraction estimation methods. The biomass fraction was estimated by the method using default values of fossil carbon fraction suggested by IPCC, the method using the solid waste composition, and the method using incinerator flue gas.

The highest biomass fractions in Korean municipal solid waste incinerator facilities were estimated by the IPCC Default method, followed by the MSW analysis method and the Flue gas analysis method. Therefore, the difference in the biomass fraction estimate was the greatest between the IPCC Default and the Flue gas analysis methods. The difference between the MSW analysis and the flue gas analysis methods was smaller than the difference with IPCC Default method. This suggested that the use of the IPCC default method cannot reflect the characteristics of Korean waste incinerator facilities and Korean MSW.

Implications: Incineration is one of most effective methods for disposal of municipal solid waste (MSW). This paper investigates the applicability of using biomass content to estimate the amount of CO₂ released, and compares the biomass contents determined by different methods in order to establish a method for estimating biomass in the MSW incinerator facilities of Korea. After analyzing the biomass contents of the collected solid waste samples and the flue gas samples, the results were compared with the Intergovernmental Panel on Climate Change (IPCC) method, and it seems that to calculate the biomass fraction it is better to use the flue gas analysis method than the IPCC method. It is valuable to design and operate a real new incineration power plant, especially for the estimation of greenhouse gas emissions.     

Public perception of smog: A case study in Ningbo City,China

Smog has become a public environmental crisis in most areas of China, and in response, research efforts have mainly focused on the chemical properties of smog and its impact on human health. However, in-depth research on the public’s perception of smog has not yet been conducted. A survey of residents living around eight state-controlled atmospheric environmental monitoring sites in Ningbo City was conducted using stratified sampling. The data was statistically analyzed to investigate people’s views and behavioral tendencies in smog weather, the influence of different media reports on public outlook, and public opinions on the local atmosphere and pollution management in different areas. The results showed that people’s perception of smog differs greatly from actual conditions, indicating that the public opinion tends to deviate when faced with a public crisis. Mainstream media (TV, newspaper, etc.), accounting for 67% of all media sources, are the main source for dissemination of smog information. The main sources of pollution, in order of decreasing contribution, according to residents of Ningbo City are as follows: motor vehicle exhaust, industrial coal combustion, large-scale construction, biomass burning, and kitchen fumes.

Implications: Since 2011, most areas of China have been affected by frequent smog. Most research on smog has been concentrated on its causes, alert systems, and prevention measures, whereas in-depth research on the public perception of smog has not yet been conducted. When a risky environmental event such as smog occurs, consequences may be more serious than the event itself will cause if people take irrational measures because of lacking relevant knowledge. Therefore, investigating people’s attitude and response to smog is both theoretically and practically significant.     

Effects of different ratios of pig manure to fungus residue on physicochemical parameters during composting

This study examined physicochemical parameters to assess their effectiveness as stability and maturity indicators during the process of composting pig manure and fungus residue at different ratios. The results showed that composting mixtures with all ratios of pig manure to fungus residue maintained a temperature exceeding 50 °C for more than 10 days during composting and met the requirement for pathogen destruction. The treatment containing mainly pig manure showed higher nitrogen loss and a shorter thermophilic phase and maturity time than the treatment containing mainly fungus residue. The germination index (GI) values indicated that compost maturity was achieved in the final compost with initial ratios of pig manure to fungus residue of 9:1–7:3 (GIs of 101.4%, 91.2%, and 81.3%); the ratio of 6:4 did not reach compost maturity (GI of 63.8%) and had an inhibitory effect on seed germination. The results of this study suggest that a ratio of pig manure to fungus residue of approximately 8:2 can be considered suitable for the efficient and quality composting of pig manure and fungus residue.

Implications: Co-composting of pig manure and edible fungi residue with appropriate proportion can effectively reduce the risk of environmental pollution caused by agricultural wastes, as well as achieve a safer and high-quality organic fertilizer, which can be used to improve physical and chemical properties of the soil, increase crop yields, and promote agricultural sustainable development. Therefore, technique of co-composting of pig manure and edible fungi residue has a wide prospect of application in practical production all over the world.     

Mapping air quality zones for coastal urban centers

This study presents a new method that incorporates modern air dispersion models allowing local terrain and land–sea breeze effects to be considered along with political and natural boundaries for more accurate mapping of air quality zones (AQZs) for coastal urban centers. This method uses local coastal wind patterns and key urban air pollution sources in each zone to more accurately calculate air pollutant concentration statistics. The new approach distributes virtual air pollution sources within each small grid cell of an area of interest and analyzes a puff dispersion model for a full year’s worth of 1-hr prognostic weather data. The difference of wind patterns in coastal and inland areas creates significantly different skewness (S) and kurtosis (K) statistics for the annually averaged pollutant concentrations at ground level receptor points for each grid cell. Plotting the S-K data highlights grouping of sources predominantly impacted by coastal winds versus inland winds. The application of the new method is demonstrated through a case study for the nation of Kuwait by developing new AQZs to support local air management programs. The zone boundaries established by the S-K method were validated by comparing MM5 and WRF prognostic meteorological weather data used in the air dispersion modeling, a support vector machine classifier was trained to compare results with the graphical classification method, and final zones were compared with data collected from Earth observation satellites to confirm locations of high-exposure-risk areas. The resulting AQZs are more accurate and support efficient management strategies for air quality compliance targets effected by local coastal microclimates.

Implications: A novel method to determine air quality zones in coastal urban areas is introduced using skewness (S) and kurtosis (K) statistics calculated from grid concentrations results of air dispersion models. The method identifies land–sea breeze effects that can be used to manage local air quality in areas of similar microclimates.     

Air quality measurements—From rubber bands to tapping the rainbow

It is axiomatic that good measurements are integral to good public policy for environmental protection. The generalized term for “measurements” includes sampling and quantitation, data integrity, documentation, network design, sponsorship, operations, archiving, and accessing for applications. Each of these components has evolved and advanced over the last 200 years as knowledge of atmospheric chemistry and physics has matured. Air quality was first detected by what people could see and smell in contaminated air. Gaseous pollutants were found to react with certain materials or chemicals, changing the color of dissolved reagents such that their light absorption at selected wavelengths could be related to both the pollutant chemistry and its concentration. Airborne particles have challenged the development of a variety of sensory devices and laboratory assays for characterization of their enormous range of physical and chemical properties. Advanced electronics made possible the sampling, concentration, and detection of gases and particles, both in situ and in laboratory analysis of collected samples. Accurate and precise measurements by these methods have made possible advanced air quality management practices that led to decreasing concentrations over time. New technologies are leading to smaller and cheaper measurement systems that can further expand and enhance current air pollution monitoring networks.

Implications: Ambient air quality measurement systems have a large influence on air quality management by determining compliance, tracking trends, elucidating pollutant transport and transformation, and relating concentrations to adverse effects. These systems consist of more than just instrumentation, and involve extensive support efforts for siting, maintenance, calibration, auditing, data validation, data management and access, and data interpretation. These requirements have largely been attained for criteria pollutants regulated by National Ambient Air Quality Standards, but they are rarely attained for nonroutine measurements and research studies.     

Development of operating mode distributions for different types of roadways under different congestion levels for vehicle emission assessment using MOVES

The Motor Vehicle Emission Simulator (MOVES) quantifies emissions as a function of vehicle modal activities. Hence, the vehicle operating mode distribution is the most vital input for running MOVES at the project level. The preparation of operating mode distributions requires significant efforts with respect to data collection and processing. This study is to develop operating mode distributions for both freeway and arterial facilities under different traffic conditions. For this purpose, in this study, we (1) collected/processed geographic information system (GIS) data, (2) developed a model of CO₂ emissions and congestion from observations, (3) implemented the model to evaluate potential emission changes from a hypothetical roadway accident scenario. This study presents a framework by which practitioners can assess emission levels in the development of different strategies for traffic management and congestion mitigation.

Implications: This paper prepared the primary input, that is, the operating mode ID distribution, required for running MOVES and developed models for estimating emissions for different types of roadways under different congestion levels. The results of this study will provide transportation planners or environmental analysts with the methods for qualitatively assessing the air quality impacts of different transportation operation and demand management strategies.     

Manganese-cerium oxide (MnOx-CeO2) catalysts supported by titanium-bearing blast furnace slag for selective catalytic reduction of nitric oxide with ammonia at low temperature

A series of manganese-cerium oxide (MnO_x-CeO₂) catalysts supported by Ti-bearing blast furnace slag were prepared by wet impregnation and used for low-temperature selective catalytic reduction (SCR) of NO with NH₃. The slag-based catalyst exhibited high nitrogen oxide removal (deNO_x) activity and wide effective temperature range. Under the condition of NO = 500 ppm, NH₃ = 500 ppm, O₂ = 7–8 vol%, and total flow rate = 1600 mL/min, the Mn-Ce/Slag catalyst exhibited a NO conversion higher than 95% in the range of 180–260 °C. The activity of Mn/Slag catalysts was greatly enhanced with the addition of CeO₂. The results indicated that Ti-bearing blast furnace slag had suitable phase composition as good support of SCR catalyst.

Implications: Ti-bearing blast furnace slag is a kind of industrial waste in China. Much slag was underused and piling up, which could cause many environmental issues, such as enormous waste of titanium and groundwater and soil contamination by heavy metals in leachates. The utilization of slag as the support of SCR catalyst will not only make use of solid waste but also cut down the NO_x emitted from power plant.     

Control of ammonia and urea emissions from urea manufacturing facilities of Petrochemical Industries Company (PIC), Kuwait

Petrochemical Industries Company (PIC) in Kuwait has mitigated the pollution problem of ammonia and urea dust by replacing the melting and prilling units of finished-product urea prills with an environmentally friendly granulation process. PIC has financed a research project conducted by the Coastal and Air Pollution Program’s research staff at the Kuwait Institute for Scientific Research to assess the impact of pollution control strategies implemented to maintain a healthy productive environment in and around the manufacturing premises. The project was completed in three phases: the first phase included the pollution monitoring of the melting and prilling units in full operation, the second phase covered the complete shutdown period where production was halted completely and granulation units were installed, and the last phase encompassed the current modified status with granulation units in full operation. There was substantial decrease in ammonia emissions, about 72%, and a 52.7% decrease in urea emissions with the present upgrading of old melting and prilling units to a state-of-the-art technology “granulation process” for a final finished product. The other pollutants, sulfur dioxide (SO₂), nitrogen oxides (NO_x), and volatile organic compounds (VOCs), have not shown any significant change, as the present modification has not affected the sources of these pollutants.

Implications: Petrochemical Industries Company (PIC) in Kuwait has ammonia urea industries, and there were complaints about ammonia and urea dust pollution. PIC has resolved this problem by replacing “melting and prilling unit” of final product urea prills by more environmentally friendly “granulation unit.” Environmental Pollution and Climate Program has been assigned the duty of assessing the outcome of this change and how that influenced ammonia and urea dust emissions from the urea manufacturing plant.     

Changes in weather and climate extremes: State of knowledge relevant to air and water quality in the United States

Air and water quality are impacted by extreme weather and climate events on time scales ranging from minutes to many months. This review paper discusses the state of knowledge of how and why extreme events are changing and are projected to change in the future. These events include heat waves, cold waves, floods, droughts, hurricanes, strong extratropical cyclones such as nor'easters, heavy rain, and major snowfalls. Some of these events, such as heat waves, are projected to increase, while others, with cold waves being a good example, will decrease in intensity in our warming world. Each extreme's impact on air or water quality can be complex and can even vary over the course of the event.

Implications:

Because extreme weather and climate events impact air and water quality, understanding how the various extremes are changing and are projected to change in the future has ramifications on air and water quality management.     

A novel bagging ensemble approach for predicting summertime ground-level ozone concentration

Ozone pollution appears as a major air quality issue, e.g. for the protection of human health and vegetation. Formation of ground level ozone is a complex photochemical phenomenon and involves numerous intricate factors most of which are interrelated with each other. Machine learning techniques can be adopted to predict the ground level ozone. The main objective of the present study is to develop the state-of-the-art ensemble bagging approach to model the summer time ground level ozone in an industrial area comprising a hazardous waste management facility. In this study, the feasibility of using ensemble model with seven meteorological parameters as input variables to predict the surface level O3 concentration. Multilayer perceptron, RTree, REPTree, and Random forest were employed as the base learners. The error measures used for checking the performance of each model includes IoAd, R2, and PEP. The model results were validated against an independent test data set. Bagged random forest predicted the ground level ozone better with higher Nash-Sutcliffe coefficient 0.93. This study scaffolded the current research gap in big data analysis identified with air pollutant prediction.

Implications: The main focus of this paper is to model the summer time ground level O₃ concentration in an Industrial area comprising of hazardous waste management facility. Comparison study was made between the base classifiers and the ensemble classifiers. Most of the conventional models can well predict the average concentrations. In this case the peak concentrations are of importance as it has serious effect on human health and environment. The models developed should also be homoscedastic.     

On ground truth in cross-border ozone transport

Cross-border transport of ozone is one of the most contentious issues of air pollution management in the U.S. Yet, both the modeling and observational studies are lacking. Models are normally validated by comparing predicted and observed ozone concentrations. However, proper validation of cross-border transport model requires a comparison of predictions against observation-based benchmarks of cross-border ozone transport. Such benchmarks are unavailable, as published observation-based studies always deal only with a combination of local production and cross-border transport, not a cross-border transport itself. We show how to extract necessary benchmarks from observations of rural monitoring sites near state borders. On example of the western border of New York, we find that in about two-thirds of the most polluted days all the ozone came in a steady cross-border inflow after previously passing over one or more large urban areas to the west. In all the enumerated days with direct cross-border inflow, daily maximum 8-hr concentrations of ozone just upwind of the border were over 60 ppb, with an average value of 68 ppb, just short of the 70 ppb ozone regulatory threshold, information also useful to state air pollution authorities.

Implications: The purpose of the cross-border ozone pollution models is to predict cross-border transport of ozone, so the ability of the model to accurately represent observed ozone concentrations is necessary but not sufficient for model validation. The accuracy of predicted ozone concentrations is not necessarily the same as the accuracy of the predictions of ozone transport. Proper model validation requires comparisons against observation-based benchmarks of cross-border transport. Such observations, so far absent, can be obtained from rural monitoring sites near state borders, as illustrated by the example of western New York.     

Association of PM2.5 pollution with the pattern of human activity: A case study of a developed city in eastern China

Recently, air pollution has attracted a substantial amount of attention in China, which can be influenced by a variety of factors, but the association between air pollution and human activity is not quite clear. Based on real-time online data (January 1, 2014, to December 31, 2014) of air pollution and meteorology reported by official sites, and demographic, economic, and environmental reform data in a statistical yearbook, the influences of meteorological factors (temperature, relative humidity, precipitation intensity, and wind force) and human activities on PM_2.5 pollution were explored. After correlation analysis, logistic regression analysis, and a nonparametric test, weak negative correlations between temperature and PM_2.5 pollution were found. In most cases, festival and morning peak hours were protection and risk factors of PM_2.5 pollution, respectively. In addition, government actions, such as an afforestation project and increasing financial expenditure for energy saving and environmental protection, could greatly contribute to alleviating pollution of PM_2.5. The findings could help officials formulate effective laws and regulations, and then PM_2.5 pollution related to the pattern of human activity would be ameliorated.

Implications: Most of the time, festival and morning peak hours are protection and risk factors for PM_2.5 pollution, respectively. Increasing the percentage of afforestation area and financial expenditure for energy saving and environmental protection could significantly reduce PM_2.5 pollution. The findings can help officials formulate effective laws and regulations, and then PM_2.5 pollution related to the pattern of human activity, especially government action, will be ameliorated.     

Emissions of organic compounds from produced water ponds II: Evaluation of flux chamber measurements with inverse-modeling techniques

In this study, the authors apply two different dispersion models to evaluate flux chamber measurements of emissions of 58 organic compounds, including C2–C11 hydrocarbons and methanol, ethanol, and isopropanol from oil- and gas-produced water ponds in the Uintah Basin. Field measurement campaigns using the flux chamber technique were performed at a limited number of produced water ponds in the basin throughout 2013–2016. Inverse-modeling results showed significantly higher emissions than were measured by the flux chamber. Discrepancies between the two methods vary across hydrocarbon compounds and are largest in alcohols due to their physical chemistries. This finding, in combination with findings in a related study using the WATER9 wastewater emission model, suggests that the flux chamber technique may underestimate organic compound emissions, especially alcohols, due to its limited coverage of the pond area and alteration of environmental conditions, especially wind speed. Comparisons of inverse-model estimations with flux chamber measurements varied significantly with the complexity of pond facilities and geometries. Both model results and flux chamber measurements suggest significant contributions from produced water ponds to total organic compound emission from oil and gas productions in the basin.

Implications: This research is a component of an extensive study that showed significant amount of hydrocarbon emissions from produced water ponds in the Uintah Basin, Utah. Such findings have important meanings to air quality management agencies in developing control strategies for air pollution in oil and gas fields, especially for the Uintah Basin in which ozone pollutions frequently occurred in winter seasons.     

A multiobjective optimization model and an orthogonal design–based hybrid heuristic algorithm for regional urban mining management problems

In this paper, a multiobjective mixed-integer piecewise nonlinear programming model (MOMIPNLP) is built to formulate the management problem of urban mining system, where the decision variables are associated with buy-back pricing, choices of sites, transportation planning, and adjustment of production capacity. Different from the existing approaches, the social negative effect, generated from structural optimization of the recycling system, is minimized in our model, as well as the total recycling profit and utility from environmental improvement are jointly maximized. For solving the problem, the MOMIPNLP model is first transformed into an ordinary mixed-integer nonlinear programming model by variable substitution such that the piecewise feature of the model is removed. Then, based on technique of orthogonal design, a hybrid heuristic algorithm is developed to find an approximate Pareto-optimal solution, where genetic algorithm is used to optimize the structure of search neighborhood, and both local branching algorithm and relaxation-induced neighborhood search algorithm are employed to cut the searching branches and reduce the number of variables in each branch. Numerical experiments indicate that this algorithm spends less CPU (central processing unit) time in solving large-scale regional urban mining management problems, especially in comparison with the similar ones available in literature. By case study and sensitivity analysis, a number of practical managerial implications are revealed from the model.

Implications: Since the metal stocks in society are reliable overground mineral sources, urban mining has been paid great attention as emerging strategic resources in an era of resource shortage. By mathematical modeling and development of efficient algorithms, this paper provides decision makers with useful suggestions on the optimal design of recycling system in urban mining. For example, this paper can answer how to encourage enterprises to join the recycling activities by government’s support and subsidies, whether the existing recycling system can meet the developmental requirements or not, and what is a reasonable adjustment of production capacity.     

Forecasting air quality time series using deep learning

This paper presents one of the first applications of deep learning (DL) techniques to predict air pollution time series. Air quality management relies extensively on time series data captured at air monitoring stations as the basis of identifying population exposure to airborne pollutants and determining compliance with local ambient air standards. In this paper, 8 hr averaged surface ozone (O₃) concentrations were predicted using deep learning consisting of a recurrent neural network (RNN) with long short-term memory (LSTM). Hourly air quality and meteorological data were used to train and forecast values up to 72 hours with low error rates. The LSTM was able to forecast the duration of continuous O₃ exceedances as well. Prior to training the network, the dataset was reviewed for missing data and outliers. Missing data were imputed using a novel technique that averaged gaps less than eight time steps with incremental steps based on first-order differences of neighboring time periods. Data were then used to train decision trees to evaluate input feature importance over different time prediction horizons. The number of features used to train the LSTM model was reduced from 25 features to 5 features, resulting in improved accuracy as measured by Mean Absolute Error (MAE). Parameter sensitivity analysis identified look-back nodes associated with the RNN proved to be a significant source of error if not aligned with the prediction horizon. Overall, MAE's less than 2 were calculated for predictions out to 72 hours.

Implications: Novel deep learning techniques were used to train an 8-hour averaged ozone forecast model. Missing data and outliers within the captured data set were replaced using a new imputation method that generated calculated values closer to the expected value based on the time and season. Decision trees were used to identify input variables with the greatest importance. The methods presented in this paper allow air managers to forecast long range air pollution concentration while only monitoring key parameters and without transforming the data set in its entirety, thus allowing real time inputs and continuous prediction.     

The relationship between atmospheric pollutant emissions and fuel qualities of inland vessels in Jiangsu Province,China

Air pollution caused by ship exhaust emission is receiving more and more attention. The physical and chemical properties of fuels, such as sulfur content and PAHs content, potentially had a significant influence on air pollutant emissions from inland vessels. In order to investigate the effects of fuel qualities on atmospheric pollutant emissions systematically, a series of experiments was conducted based on the method of actual ship testing. As a result, SO2, PM and NOx emission rates all increased with the increase of main engine rotating speed under cruise mode, while PM and NOx emission factors were inversely proportional to the main engine rotating speed. Moreover, SO2 emission factor changed little with the increase of the main engine rotating speed. In summary, the fuel-dependent specific emission of SO2 was a direct reflection of the sulfur content in fuel. The PM emission increased with the increase of sulfur content and PAHs content in fuel. However, fuel qualities impacted little on NOx emissions from inland vessels because of NOx formation mechanisms and conditions.

Implications: Ship activity is considered to be the third largest source of air pollution in China. In particular, air pollutants emitted from ships in river ports and waterways have a direct impact on regional air quality and pose threat on the health of local residents owing to high pollutants concentration and poor air diffusion. The study on the relationship between air pollutant emissions and fuel quality of inland vessels can provide foundational data for local authority to formulate reasonable and appropriate policies for reducing atmospheric pollution due to inland vessels.