Assessing the intra-urban variability of nitrogen oxides and ozone across a highly heterogeneous urban area.

High-resolution air quality maps are critical towards assessing and understanding exposures to elevated air pollution in dense urban areas. However, these surfaces are rarely available in low- and middle-income countries that suffer from some of the highest air pollution levels worldwide. In this study, we make use of land use regressions (LURs) to generate annual and seasonal, high-resolution nitrogen dioxide (NO2), nitrogen oxides (NOx), and ozone (O3) exposure surfaces for the Greater Beirut Area (GBA) in Lebanon. NO2, NOx and O3 concentrations were monitored using passive samplers that were deployed at 55 pre-defined monitoring locations. The average annual concentrations of NO2, NOx, and O3 across the GBA were 36.0, 89.7, and 26.9 ppb, respectively. Overall, the performance of the generated models was appropriate, with low biases, high model robustness, and acceptable R2 values that ranged between 0.66 and 0.73 for NO2, 0.56 and 0.60 for NOx, and 0.54 and 0.65 for O3. Traffic-related emissions as well as the operation of a fossil-fuel power plant were found to be the main contributors to the measured NO2 and NOx levels in the GBA, whereas they acted as sinks for O3 concentrations. No seasonally significant differences were found for the NO2 and NOx pollution surfaces; as their seasonal and annual models were largely similar (Pearson's r > 0.85 for both pollutants). On the other hand, seasonal O3 pollution surfaces were significantly different. The model results showed that around 99% of the population of the GBA were exposed to NO2 levels that exceeded the World Health Organization defined annual standard.

Drivers of seasonal and annual air pollution exposure in a complex urban environment with multiple source contributions.

Outdoor air pollution is a global health concern, but detailed exposure information is still limited for many parts of the world. In this study, high-resolution exposure surfaces were generated for annual and seasonal fine particulate matter (PM2.5), coarse particulate matter (PM10), and carbon monoxide (CO) for the Greater Beirut Area (GBA), Lebanon, an urban zone with a complex topography and multiple source contributions. Land use regression models (LUR) were calibrated and validated with monthly data collected from 58 locations between March 2017 and March 2018. The annual mean (±1 SD) concentrations of PM2.5, PM10, and CO across the monitoring locations were 68.1 (±15.7) µg/m3, 83.5 (±19.5) µg/m3, and 2.48 (±1.12) ppm, respectively. The coefficients of determination for LUR models ranged from 56 to 67% for PM2.5, 44 to 63% for the PM10 models, and 50 to 60% for the CO. LUR model structures varied significantly by season for both PM2.5 and PM10 but not for CO. Traffic emissions were consistently the main source of CO emissions throughout the year. The relative importance of industrial emissions and power generation sources towards predicted PM levels increased during the hot season while the contribution of the international airport diminished. Moreover, the complex topography of the study area along with the seasonal changes in the predominant wind directions affected the spatial predicted concentrations of all three pollutants. Overall, the predicted exposure surfaces were able to conserve the inter-pollution correlations determined from the field monitoring campaign, with the exception of the cold season. Our pollution surfaces suggest that the entire population of Beirut is regularly exposed to concentrations exceeding the World Health Organization (WHO) air quality standards for both PM2.5 and PM10.

Global municipal solid waste infrastructure: Delivery and forecast of uncontrolled disposal.

Proper management and treatment of municipal solid waste (MSW) plays a central role towards the reduction or elimination of uncontrolled disposal and the achievement of United Nations (UN) Sustainable Development Goals (SDGs) with the reduction of its vast adverse environmental and health impacts. Despite that, till now, there has never been a quantitative analysis of the progress in waste management infrastructure delivery worldwide. In this paper, we provide valuable insights regarding the progress in new MSW infrastructure delivery based on a dataset of 1764 projects from 156 countries, for the period 2014-2019. We also estimate the magnitude of uncontrolled waste disposal practices worldwide by estimating the gap between the current MSW infrastructure delivery and actual changes in MSW generation. Our results show that the new capacity delivered during the six years period amounted to 243 million metric tonnes (Mt) (40 million Mt per year), out of which 45% was delivered in high-income countries, 37.5% in the People's Republic of China and 17.5% in the rest of the world, mainly through thermal treatment (~57%) and landfilling (8%). The average allocated per capita budget of these projects during this period is about US$14, equivalent to US$2.33 (cap*year)-1. Our main conclusion is that the share of uncontrolled disposal will continue to rise at least until 2028, reaching almost 730 million Mt per year. Evidently, the global community continues to face a serious challenge towards the implementation of the UN SDG 12, target 12.4 by 2020. The analysis demonstrates that infrastructure delivery must increase by four folds to eliminate uncontrolled disposal practices.

Life cycle assessment for solid waste management in Lebanon: Economic implications of carbon credit.

Solid waste management has witnessed much progress in recent years with considerable efforts targeting the reduction of associated impacts and carbon emissions. Such efforts remain relatively limited in developing economies due to inefficient management practices. In this study, a life cycle assessment (LCA) approach is adopted to identify integrated systems with minimal impacts and reduced emissions in a developing context coupled with an economic valuation and sensitivity analysis to assess the effect of varying influencing parameters individually. The results showed that the highest impact arises from landfilling with minimal material recovery for recycling and composting, while incineration coupled with energy recovery contributed to the least equivalent emissions (-111% with respect to baseline scenario) at a varying cost of -70% to +93% depending on the selected technology and the value of carbon credit. Optimizing material recycling, composting and landfilling with energy recovery contributed to 98% savings in emissions (with respect to baseline scenario) and remained economically attractive irrespective of the carbon credit exchange rate of 0.5-50 US$/MTCO2E. The sensitivity analysis showed that an improvement in landfill gas collection efficiency (up to 60%) can contribute to major savings in emissions (58%). The application of the LCA-based approach supports the development of integrated viable plans while quantifying advantages and disadvantages towards decision-making and policy-planning.

Economic and environmental consequences of implementing an EU model for collecting and separating wastes system in Lebanon.

In this study, we examine the economic and environmental significance associated with the implementation of an EU waste-separated collection scheme in a developing context - Lebanon. Two scenarios, S1 and S2, representing different intensities of source segregation were analysed. In S1, the average source segregation intensity reached 25% and 13% for the Italian test area and Lebanese test area, respectively. In S2, source segregation intensity increased to 48% and 68% for the Italian and Lebanese test areas, respectively. Passing from S1 to S2 increased collection costs significantly, up to 44% with greater increases in the Italian test area where labour cost is higher. In both areas, environmental impacts decreased with greater source segregation intensity. Savings in the climate change impact and stratospheric ozone depletion potential were lower under the Lebanese test area in comparison with the Italian test area. In contrast, savings in freshwater eutrophication and acidification impact were lower for the Italian test area. The increase in the source segregation intensity resulted in maximum savings for the depletion of abiotic resources, 74% to 77% and 79% to 80% in a developing and developed context, respectively.

Correlation between system performance and bacterial composition under varied mixing intensity in thermophilic anaerobic digestion of food waste.

This study examines the stability and efficiency of thermophilic anaerobic digesters treating food waste under various mixing velocities (50-160 rpm). The results showed that high velocities (120 and 160 rpm) were harmful to the digestion process with 18-30% reduction in methane generation and 1.8 to 3.8 times increase in volatile fatty acids (VFA) concentrations, compared to mild mixing (50 and 80 rpm). Also, the removal rate of soluble COD dropped from 75 to 85% (at 50-80 rpm) to 20-59% (at 120-160 rpm). Similarly, interrupted mixing caused adverse impacts and led to near-failure conditions with excessive VFA accumulation (15.6 g l-1), negative removal rate of soluble COD and low methane generation (132 ml gVS-1). The best efficiency and stability were achieved under mild mixing (50 and 80 rpm). In particular, the 50 rpm stirring speed resulted in the highest methane generation (573 ml gVS-1). High-throughput sequencing of 16S rRNA genes revealed that the digesters were dominated by one bacterial genus (Petrotoga; phylym Thermotogae) at all mixing velocities except at 0 rpm, where the community was dominated by one bacterial genus (Anaerobaculum; phylum Synergistetes). The Petrotoga genus seems to have played a major role in the degradation of organic matter.

Monitoring water quality in a hypereutrophic reservoir using Landsat ETM+ and OLI sensors: how transferable are the water quality algorithms?

The launch of the Landsat 8 in February 2013 extended the life of the Landsat program to over 40 years, increasing the value of using Landsat to monitor long-term changes in the water quality of small lakes and reservoirs, particularly in poorly monitored freshwater systems. Landsat-based water quality hindcasting often incorporate several Landsat sensors in an effort to increase the temporal range of observations; yet the transferability of water quality algorithms across sensors remains poorly examined. In this study, several empirical algorithms were developed to quantify chlorophyll-a, total suspended matter (TSM), and Secchi disk depth (SDD) from surface reflectance measured by Landsat 7 ETM+ and Landsat 8 OLI sensors. Sensor-specific multiple linear regression models were developed by correlating in situ water quality measurements collected from a semi-arid eutrophic reservoir with band ratios from Landsat ETM+ and OLI sensors, along with ancillary data (water temperature and seasonality) representing ecological patterns in algae growth. Overall, ETM+-based models outperformed (adjusted R2 chlorophyll-a = 0.70, TSM = 0.81, SDD = 0.81) their OLI counterparts (adjusted R2 chlorophyll-a = 0.50, TSM = 0.58, SDD = 0.63). Inter-sensor differences were most apparent for algorithms utilizing the Blue spectral band. The inclusion of water temperature and seasonality improved the power of TSM and SDD models.

The role of the water tankers market in water stressed semi-arid urban areas:Implications on water quality and economic burden.

Population growth and development are associated with increased water demand that often exceeds the capacity of existing resources, resulting in water shortages, particularly in urban areas, where more than 60% of the world's population resides. In many developing communities, shortages often force households to depend on water tankers amongst other potential sources for the delivery of water for domestic and/or potable use. While water tankers have become an integral part of the water supply system in many countries, the sector is often unregulated and operates with little governmental supervision. Users are invariably unaware of the origin or the quality of purchased water. In an effort to better assess this sector, a field survey of water vending wells and tankers coupled with a water quality sampling and analysis program was implemented in a pilot semi-arid urban area (Beirut, Lebanon) to shed light on the environmental and socio-economic impacts of the water tanker sector. Total dissolved solids (TDS), chloride (Cl-), and microbial loads exceeded drinking water quality standards. While TDS and Cl- levels were mostly due to saltwater intrusion in coastal wells, tankers were found to be a significant source of total coliforms. Delivered water costs varied depending on the tanker size, the quality of the distributed water, and pre-treatment used, with a markup of nearly 8-24 folds of the public water supply and an equivalent economic burden of 16% of the average household income excluding environmental externalities of water quality. The study concludes with a management framework towards consumer protection under integrated supply and demand side measures.

Social Perception of Public Water Supply Network and Groundwater Quality in an Urban Setting Facing Saltwater Intrusion and Water Shortages.

Perceptions developed by consumers regarding the quality of water reaching their household can affect the ultimate use of the water. This study identified key factors influencing consumers' perception of water quality in a highly urbanized coastal city, experiencing chronic water shortages, overexploitation of groundwater, and accelerated saltwater intrusion. Household surveys were administered to residents to capture views and perceptions of consumed water. Concomitantly, groundwater and tap water samples were collected and analyzed at each residence for comparison with perceptions. People's rating of groundwater quality was found to correlate to the measured water quality both in the dry and wet seasons. In contrast, perceptions regarding the water quality of the public water supply network did not show any correlation with the measured tap water quality indicators. Logistic regression models developed to predict perception based on salient variables indicated that age, apartment ownership, and levels of total dissolved solids play a significant role in shaping perceptions regarding groundwater quality. Perceptions concerning the water quality of the public water supply network appeared to be independent of the measured total dissolved solids levels at the tap but correlated to those measured in the wells. The study highlights misconceptions that can arise as a result of uncontrolled cross-connections of groundwater to the public supply network water and the development of misaligned perceptions based on prior consumption patterns, water shortages, and a rapidly salinizing groundwater aquifer.

A propidium monoazide-quantitative PCR method for the detection and quantification of viable Enterococcus faecalis in large-volume samples of marine waters.

The development of rapid detection assays of cell viability is essential for monitoring the microbiological quality of water systems. Coupling propidium monoazide with quantitative PCR (PMA-qPCR) has been successfully applied in different studies for the detection and quantification of viable cells in small-volume samples (0.25-1.00 mL), but it has not been evaluated sufficiently in marine environments or in large-volume samples. In this study, we successfully integrated blue light-emitting diodes for photoactivating PMA and membrane filtration into the PMA-qPCR assay for the rapid detection and quantification of viable Enterococcus faecalis cells in 10-mL samples of marine waters. The assay was optimized in phosphate-buffered saline and seawater, reducing the qPCR signal of heat-killed E. faecalis cells by 4 log10 and 3 log10 units, respectively. Results suggest that high total dissolved solid concentration (32 g/L) in seawater can reduce PMA activity. Optimal PMA-qPCR standard curves with a 6-log dynamic range and detection limit of 10(2) cells/mL were generated for quantifying viable E. faecalis cells in marine waters. The developed assay was compared with the standard membrane filter (MF) method by quantifying viable E. faecalis cells in seawater samples exposed to solar radiation. The results of the developed PMA-qPCR assay did not match that of the standard MF method. This difference in the results reflects the different physiological states of E. faecalis cells in seawater. In conclusion, the developed assay is a rapid (∼5 h) method for the quantification of viable E. faecalis cells in marine recreational waters, which should be further improved and tested in different seawater settings.

Pilot-based assessment of the economics of recycling construction demolition waste.

The significant amount of waste generated from construction demolition has become a chronic problem in many developing countries. Using data obtained from demolition contractors and various other sources, this paper proposes a framework for proper handling of construction demolition waste (CDW) to serve as a decision support tool in countries suffering from the lack of national CDW management guidelines. The framework is then demonstrated through a case study in the city of Beirut, Lebanon, and a sensitivity analysis is carried out to examine the economic feasibility of developing a recycling facility. The analysis showed that in order for a facility to be feasible, a gate fee should be charged in the presence of a market for recycled aggregates. The results confirm the significance of instigating and implementing legislation to control illegal dumping, constructing, and managing engineered landfills, and establishing markets for recycled CDW.

Hollow-fiber membrane bioreactor for the treatment of high-strength landfill leachate.

Performance assessment of membrane bioreactor (MBR) technology for the treatability of high-strength landfill leachate is relatively limited or lacking. This study examines the feasibility of treating high-strength landfill leachate using a hollow-fiber MBR. For this purpose, a laboratory-scale MBR was constructed and operated to treat leachate with a chemical oxygen demand (COD) of 9000-11,000 mg/l, a 5-day biochemical oxygen demand (BOD5) of 4000-6,000 mg/l, volatile suspended solids (VSS) of 300-500 mg/l, total nitrogen (TN) of 2000-6000 mg/l, and an ammonia-nitrogen (NH3-N) of 1800-4000 mg/l. VSS was used with the BOD and COD data to simulate the biological activity in the activated sludge. Removal efficiencies > 95-99% for BOD5, VSS, TN and NH3-N were attained. The coupled experimental and simulation results contribute in filling a gap in managing high-strength landfill leachate and providing guidelines for corresponding MBR application.

Enhanced solid waste stabilization in aerobic landfills using low aeration rates and high density compaction.

Historically, municipal solid waste landfills have been designed and operated as storage facilities with suboptimal degradation under anaerobic conditions resulting in slow waste stabilization, gaseous emissions and leachate formation. This article examines the aerobic bioreactor alternative combining the recirculation of high strength leachate [chemical oxygen demand (COD): 89,000-95,600 mg/l; biological oxygen demand (BOD): 75,700-80,000 mg/l)] with low aeration rates (0.0125-0.05 l/min.kg) at high initial waste compaction (657-875 kg/m3) to promote and control biodegradation of solid waste in laboratory-scale columns (diameter = 60 cm, height = 1 m). Low aeration rates coupled with high initial density demonstrated improved performance with increased levels of stabilization with COD and BOD attenuation reaching up to 96%, final C:N ratio of 25 and waste settlement up to 55%.

Airborne influenza virus shedding by patients in health care units: Removal mechanisms affecting virus transmission.

In this study, we characterize the distribution of airborne viruses (influenza A/B) in hospital rooms of patients with confirmed infections. Concurrently, we monitored fine particulate matter (PM2.5 & PM10) and several physical parameters including the room air exchange rate, temperature, and relative humidity to identify corresponding correlations with virus transport and removal determinants. The results continue to raise concerns about indoor air quality (IAQ) in healthcare facilities and the potential exposure of patients, staff and visitors to aerosolized viruses as well as elevated indoor PM levels caused by outdoor sources and/or re-suspension of settled particles by indoor activities. The influenza A virus was detected in 42% of 33 monitored rooms, with viruses detectible up to 1.5 m away from the infected patient. Active coughing was a statistically significant variable that contributed to a higher positive rate of virus detection in the collected air samples. Viral load across patient rooms ranged between 222 and 5,760 copies/m3, with a mean of 820 copies/m3. Measured PM2.5 and PM10 levels exceeded IAQ daily exposure guidelines in most monitored rooms. Statistical and numerical analyses showed that dispersion was the dominant viral removal pathway followed by settling. Changes in the relative humidity and the room's temperature were had a significant impact on the viral load removal. In closure, we highlight the need for an integrated approach to control determinants of IAQ in patients' rooms.

Dynamic Bayesian Networks to Assess Anthropogenic and Climatic Drivers of Saltwater Intrusion: A Decision Support Tool Toward Improved Management.

Saltwater intrusion (SWI) is a global coastal problem caused by aquifer overpumping, land-use change, and climate change impacts. Given the complex pathways that lead to SWI, coastal urban areas with poorly monitored aquifers are in need of probabilistic-based decision support tools that can assist in better understanding and predicting SWI, while exploring effective means for sustainable aquifer management. In this study, we develop a Bayesian Belief Network (BBN) to account for the complex interactions of climatic and anthropogenic processes leading to SWI, while relating the severity of SWI to associated socioeconomic impacts and possible adaptation strategies. The BBN is further expanded into a Dynamic Bayesian Network (DBN) to assess the temporal progression of SWI and account for the compounding uncertainties over time. The proposed DBN is then tested at a pilot coastal aquifer underlying a highly urbanized water-stressed metropolitan area along the Eastern Mediterranean coastline (Beirut, Lebanon). The results show that the future impacts of climate change are largely secondary when compared to the persistent water deficits. While both supply and demand management could halt the progression of salinity, the potential for reducing or reversing SWI is not evident. The indirect socioeconomic burden associated with aquifer salinity was observed to improve, albeit heterogeneously, with the application of various adaptation strategies; however, this was at a cost associated with the implementation and operation of these strategies. The proposed DBN acts as an effective decision support tool that can promote sustainable aquifer management in coastal regions through its robust representation of the main drivers of SWI and linking them to expected socioeconomic burdens and management options. Integr Environ Assess Manag 2021;17:202-220. © 2020 SETAC.

Optimizing emissions and carbon credit from integrated solid waste and wastewater management: A MATLAB-based model with a Graphical User Interface (v1).

A new Solid Waste and Wastewater (SWW) management software is presented for optimizing the life-cycle of emissions with carbon credit cost considerations. The software is the first to combine integrated solid waste and wastewater management systems under a single framework when introducing a food waste disposer (FWD) policy. The model/software offers a platform encompassing several tools for life cycle emissions accounting, optimization, as well as economic, policy, and sensitivity analysis. It provides the flexibility of selecting processes or modifying input parameters, as well as disaggregating emissions depending on the scope of accounting. The graphical user interface is applicable in the context of developed and developing economies with the ultimate objective to assist decision makers to allocate expenditures for emissions mitigation measures.

A novel software for optimizing emissions and carbon credit from solid waste and wastewater management.

A novel model/software that assesses emissions from integrated solid waste and wastewater, SWW, management systems is presented. The main objective of SWW is to optimize emissions and carbon credit of complex systems. Besides its general applicability, the software covers the lack of available tools applicable in the context of developing economies. It uses carbon credit as a measure of environmental valuation and provides a user-friendly platform supported with several tools for technical, economic, and policy analysis as well as optimization towards minimal total emissions or costs. Finally, it encompasses a sensitivity analysis with a built-in Monte Carlo simulation to check on the variability in emissions by varying key parameters. The model/software interface was tested in the context of developed and developing economies. The results showed that best practices through material recycling, biological treatment, food waste diverted and/or energy recovery can lead to substantial savings in emissions reaching 96% (under a developing economy) and 93% (under a developed economy), with cost savings (including carbon credit) reaching 26% (under a developing economy) and 4% (under a developed economy), depending on the system. In closure, the results demonstrated the model applicability as a credible decision-making tool to define economically viable management alternatives with minimal environmental externalities and optimal carbon credit.

Data-Worth Assessment for a Three-Dimensional Optimal Design in Nonlinear Groundwater Systems.

Groundwater model predictions are often uncertain due to inherent uncertainties in model input data. Monitored field data are commonly used to assess the performance of a model and reduce its prediction uncertainty. Given the high cost of data collection, it is imperative to identify the minimum number of required observation wells and to define the optimal locations of sampling points in space and depth. This study proposes a design methodology to optimize the number and location of additional observation wells that will effectively measure multiple hydrogeological parameters at different depths. For this purpose, we incorporated Bayesian model averaging and genetic algorithms into a linear data-worth analysis in order to conduct a three-dimensional location search for new sampling locations. We evaluated the methodology by applying it along a heterogeneous coastal aquifer with limited hydrogeological data that is experiencing salt water intrusion (SWI). The aim of the model was to identify the best locations for sampling head and salinity data, while reducing uncertainty when predicting multiple variables of SWI. The resulting optimal locations for new observation wells varied with the defined design constraints. The optimal design (OD) depended on the ratio of the start-up cost of the monitoring program and the installation cost of the first observation well. The proposed methodology can contribute toward reducing the uncertainties associated with predicting multiple variables in a groundwater system.

In-vehicle CO ingression: validation through field measurements and mass balance simulations.

In this study a mass balance modeling approach with measured out-vehicle carbon monoxide (CO) levels and trip-specific movement record as boundary conditions were used to simulate in-vehicle CO concentration profiles. The simulation results were coupled with field measurements to demonstrate the occurrence of CO ingression into the vehicle compartment from the engine combustion and/or exhaust return of the test vehicle. Agreement between field and simulation results was obtained for variable amounts of infiltrated CO equivalent to an in-vehicle emission rate of 250 to 1250 mg/h of CO depending on the vehicle ventilation settings.

Aggregated and disaggregated data about default emission factors in emissions accounting methods from the waste sector.

The dataset presented in this article is related to the research article entitled "Towards improving emissions accounting methods in waste management: A proposed framework" (Maalouf and El-Fadel, 2019) [1] that examines the variability in aggregated and disaggregated emissions from waste management when using commonly adopted international methods (the UN IPCC 2006 Guidelines, the US EPA WARM, the EU EpE protocols, the Canadian IWM, and the UK IWM-2). The dataset presents the aggregated and disaggregated emission factors (EFs) used in existing accounting methods to estimate emissions from the waste sector. The EFs were retrieved from accounting methods to clarify their contribution to variability in estimating emissions across methods. The data contains three parts: aggregated EFs per tonne of waste category for individual waste management processes; disaggregated EFs per management process for a tonne of waste type; and emission flow diagrams of waste management systems for tested methods.