Objectives:To compare water quality parameters in the vicinity of Gas Flaring Area of Ebocha-Obrikom of Rivers State with that of the recommended standards.Methods:The research utilized standard analytical procedures. All sampling, conservation, transportation and analysis followed standard procedures described in APHA (2012). All the samples collected were transported to the laboratory through keeping in an icebox to prevent degradation of the organic substances.Results:Result depicts that Turbidity, DO, BOD, COD, TSS, Magnesium, Iron, Cadmium, Lead, Chromium, and Nickel exceeded the desirable limit meant for drinking purpose as well as could potentially pose threats toward human society. Hence, remain unsuitable for drinking, as the inhabitants were more vulnerable for their total lifetime period of exposure through continuous consumption of unsuitable drinking water.Conclusion:It is recommended that the local government environmental health officers and other regulatory agencies frequently monitor the levels of these pollutants within the area and also ensure strict adherence to guidelines to ensure a healthy environment. As exposure to the above stated parameters can have a remarkable impact on human health living in the vicinity of the gas flaring area by drinking water around the study area; thus, groundwater needs to treated before using for household purpose or drinking. Thus, this study would help in decision making for stakeholders and relevant authorities in the execution of reasonable groundwater management strategies and remediation plans in the area to protect public and environmental health.

It is widely recognized that green infrastructures in urban ecosystems provides important ecosystem services, including air purification. The potential absorption of nitrogen oxides (NOₓ) by urban trees has not been fully quantified, although it is important for air pollution mitigation and the well-being of urban residents. In this study, four common tree species (Sophora japonica L., Fraxinus chinensis Roxb., Populus tomentosa Carrière, Sabina chinensis (L.)) in Beijing, China, were studied. The dual stable isotopes (¹⁵N and ¹⁸O) and a Bayesian isotope mixing model were applied to estimate the sources contributions of potential nitrogen sources to the roadside trees based on leaf and soil sampling in urban regions. The following order of sources contributions was determined: soil > dry deposition > traffic-related NOₓ. The capacity of urban trees for NOₓ removal in the city was estimated using a remote sensing and GIS approach, and the removal capacity was found to range from 0.79 to 1.11 g m⁻² a⁻¹ across administrative regions, indicating that 1304 tons of NOₓ could be potentially removed by urban trees in 2019. Our finding qualified the potential NOₓ removal by urban trees in terms of atmospheric pollution mitigation, highlighting the role of green infrastructure in air purification, which should be taken into account by stakeholders to manage green infrastructure as the basis of a nature-based approach.

Flaring is a common and necessary operation for chemical industries, which is designed to manage dangerous process overpressure scenarios or to release and destroy off-spec products during chemical plant upsets or turnarounds. However, excessive flaring can emit large quantities of VOCs and NOx into the atmosphere, which will cause transient and localized ozone pollution events in the presence of sunlight. The objective of this study was to quantify the impact to regional air-quality due to flare emissions from chemical plant start-up operations through the coupling of dynamic process simulations via Aspen Plus and air-quality simulations via CAMx. Simulation results from case studies have indicated that the corresponding ozone increments can vary significantly from 0.2 ppb to 17.8 ppb under different temporal and spatial factors, including the start-up starting hour, starting day, and plant location. Additional ozone sensitivity simulations have also indicated that the corresponding ozone increments are higher when the plant is located in a VOC-limited area than that in a NOx-limited area. The results from this study have delivered a cost-effective air-quality control practice for plant start-ups with a minimum air-quality impact through selecting the optimal starting time within the allowable ranges. The practice has significant potential to benefit all stakeholders, including environmental agencies, chemical industries, and local communities.

The state of practice for noise assessment utilizes established standards for emission and propagation modelling of linear and point sources. Recently, land use regression (LUR) modelling has emerged as an alternative method due to relatively low data and computing resource demands. However, a limitation of LUR modelling is that is does not account for noise attenuation and reflections by features of the built environment. This study demonstrates and validates a method that combines the two modelling frameworks to exploit their respective strengths: Emission and propagation based prediction of traffic noise, the predominant source of noise at the level of streetscapes, and a LUR-based correction for noise sources that vary on spatial scales beyond the streetscape.Multi-criteria analysis, location-allocation modelling and stakeholder consultation identified 220 monitoring sites with optimal coverage for a 1-week sampling period. A subset of sites was used to validate a road traffic noise emission and propagation model and to specify a LUR model that predicted the contribution of other sources. The equivalent 24-h sound pressure level (LAeq) for all sites was 62.9 dBA (SD 6.4). This varied by time of day, weekday, types of roads and land uses. The traffic noise emission model demonstrated a high level of covariance with observed noise levels, with R² values of 0.58, 0.60 and 0.59 for daytime, nighttime and 24-h periods, respectively. Combined with LUR models to correct for other noise sources, the hybrid models R² values were 0.64, 0.71 and 0.67 for the respective time periods.The study showed that road traffic noise emissions account for most of the variability of total environmental noise in Toronto. The combined approach to predict fine resolution noise exposures with emission and receptor-based models presents an effective alternative to noise modelling approaches based on emission and propagation or LUR modelling.

Residential woodsmoke is an under-regulated source of fine particulate matter (PM2.5), often surpassing mobile and industrial emissions in rural communities in North America and elsewhere. In the province of British Columbia (BC), Canada, many municipalities are hesitant to adopt stricter regulations for residential wood burning without empirical evidence that smoke is affecting local air quality. The objective of this study was to develop a retrospective algorithm that uses 1-h PM2.5 concentrations and daily temperature data to identify smoky days in order to prioritise communities by smoke impacts. Levoglucosan measurements from one of the smokiest communities were used to establish the most informative values for three algorithmic parameters: the daily standard deviation of 1-h PM2.5 measurements; the daily mean temperature; and the daytime-to-nighttime ratio of PM2.5 concentrations. Alternate parameterizations were tested in 45 sensitivity analyses. Using the most informative parameter values on the most recent two years of data for each community, the number of smoky days ranged from 5 to 277. Heat maps visualizing seasonal and diurnal variation in PM2.5 concentrations showed clear differences between the higher- and lower-ranked communities. Some communities were sensitive to one or more of the parameters, but the overall rankings were consistent across the 45 analyses. This information will allow stakeholder agencies to work with local governments on implementing appropriate intervention strategies for the most smoke-impacted communities.

Air pollutants emitted from vehicles in street canyons may be reactive, undergoing mixing and chemical processing before escaping into the overlying atmosphere. The deterioration of air quality in street canyons occurs due to combined effects of proximate emission sources, dynamical processes (reduced dispersion) and chemical processes (evolution of reactive primary and formation of secondary pollutants). The coupling between dynamics and chemistry plays a major role in determining street canyon air quality, and numerical model approaches to represent this coupling are reviewed in this article. Dynamical processes can be represented by Computational Fluid Dynamics (CFD) techniques. The choice of CFD approach (mainly the Reynolds-Averaged Navier-Stokes (RANS) and Large-Eddy Simulation (LES) models) depends on the computational cost, the accuracy required and hence the application. Simplified parameterisations of the overall integrated effect of dynamics in street canyons provide capability to handle relatively complex chemistry in practical applications. Chemical processes are represented by a chemical mechanism, which describes mathematically the chemical removal and formation of primary and secondary species. Coupling between these aspects needs to accommodate transport, dispersion and chemical reactions for reactive pollutants, especially fast chemical reactions with time scales comparable to or shorter than those of typical turbulent eddies inside the street canyon. Different approaches to dynamical and chemical coupling have varying strengths, costs and levels of accuracy, which must be considered in their use for provision of reference information concerning urban canopy air pollution to stakeholders considering traffic and urban planning policies.

The purpose of this paper is to integrate the concepts of ecosystem services and disservices when assessing the efficacy of using urban forests for mitigating pollution. A brief review of the literature identifies some pollution mitigation ecosystem services provided by urban forests. Existing ecosystem services definitions and typologies from the economics and ecological literature are adapted and applied to urban forest management and the concepts of ecosystem disservices from natural and semi-natural systems are discussed. Examples of the urban forest ecosystem services of air quality and carbon dioxide sequestration are used to illustrate issues associated with assessing their efficacy in mitigating urban pollution. Development of urban forest management alternatives that mitigate pollution should consider scale, contexts, heterogeneity, management intensities and other social and economic co-benefits, tradeoffs, and costs affecting stakeholders and urban sustainability goals.

Nitrogen pollution caused serious environmental problems in reservoir ecosystems. Reducing nitrogen pollution by enhancing nitrogen removal in river sediments deserved intensive research. Distributions of nitrogen contents in sediment-water interface were characterized along the Xiangxi bay (XXB), a eutrophic tributary in Three Gorges Reservoir, China. More than 47% of total Kjeldahl nitrogen (TKN) and 67% of total organic nitrogen (TON) were degraded during burial. Higher TN, TON and NH₄⁺ consuming at downstream sites indicated stronger nitrogen mineralization and release due to higher turbulence of the overlying density currents. Nitrifying bacteria, denitrifying bacteria, anaerobic ammonium oxidizing (anammox) bacteria and nitrite/nitrate-dependent anaerobic methane oxidation (N-DAMO) bacteria were detected in nitrate-ammonium transition zone. Nitrogen contents transitions were responded to microbial stakeholders indicated microbially mediated nitrogen cycling in sediments. The dissolved oxygen and nitrate availabilities were the key limits of denitrification and associated reactions. These results suggested microbial mediated nitrogen cycling processes in sediments were critical for nitrogen removal in aquatic ecosystems, and replenishing dissolved oxygen and nitrate was expected to enhance sediment denitrification and strengthen potential environmental self-purification.

Current mitigation strategies to offset marine plastic pollution, a global concern, typically rely on preventing floating debris from reaching coastal ecosystems. Specifically, clean-up technologies are designed to collect plastics by removing debris from the aquatic environment such as rivers and estuaries. However, to date, there is little published data on their potential impact on riverine and estuarine organisms and ecosystems. Multiple parameters might play a role in the chances of biota and organic debris being unintentionally caught within a mechanical clean-up system, but their exact contribution to a potential impact is unknown. Here, we identified four clusters of parameters that can potentially determine the bycatch: (i) the environmental conditions in which the clean-up system is deployed, (ii) the traits of the biota the system interacts with, (iii) the traits of plastic items present in the system, and, (iv) the design and operation of the clean-up mechanism itself. To efficiently quantify and assess the influence of each of the clusters on bycatch, we suggest the use of transparent and objective tools. In particular, we discuss the use of Bayesian Belief Networks (BBNs) as a promising probabilistic modelling method for an evidence-based trade-off between removal efficiency and bycatch. We argue that BBN probabilistic models are a valuable tool to assist stakeholders, prior to the deployment of any clean-up technology, in selecting the best-suited mechanism to collect floating plastic debris while managing potential adverse effects on the ecosystem.

The versatile use of various synthetic polymers, including plastics, generates a large volume of non-degradable waste, which is eventually responsible for forming microplastics (MPs) in aquatic environments. The present study describes the significant spatial and seasonal variation on the abundance of MPs and their physiochemical nature along the Mandovi-Zuari estuarine system of Goa, west coast of India. During the wet season (September), the average abundance of MPs was found relatively higher in water (0.107 particles/m³) and sediment (7314 particles/kg) than those found in the dry season (April) (0.099 particles/m³ in water and 4873 particles/kg in sediment). During the wet season, heavy rain and excessive riverine freshwater influx carry more terrestrial plastic debris in the estuarine system which causes higher averages MPs density in surface water and sediment. <300 μm sized particles and black colored MPs were predominant equally in water and sediment during both seasons. MPs of different shapes like fragments, fibres, films and beads accounted for most collected samples. The Micro-Fourier Transform Infrared Spectroscopy (μ-FTIR) based compositional analysis identified approximately 33 types of polymers, of which polyacrylamide (PAM), polyacetylene, polyamide (PA), polyvinyl pyrrolidone (PVP), polyvinyl chloride (PVC), and polyimide (PI) were abundant. Fragmentation of larger plastic particles due to mismanaged treated and untreated STPs and washing machine effluents are the primary sources of these MPs in the estuarine system. Moreover, these estuaries also receive a variety of domestic, industrial and other wastes from local cities, ports, and fishing jetties. Thus the present study enlightens the current distribution of MPs and their sources in the Mandovi-Zuari estuarine system and thus provides very useful information to the stakeholder and concerned departments for initiating the mitigation measures.