Effluent parameters prediction of a biological nutrient removal (BNR) process using different machine learning methods: A case study.

This paper proposes a novel targeted blend of machine learning (ML) based approaches for controlling wastewater treatment plant (WWTP) operation by predicting distributions of key effluent parameters of a biological nutrient removal (BNR) process. Two years of data were collected from Plajyolu wastewater treatment plant in Kocaeli, Türkiye and the effluent parameters were predicted using six machine learning algorithms to compare their performances. Based on mean absolute percentage error (MAPE) metric only, support vector regression machine (SVRM) with linear kernel method showed a good agreement for COD and BOD5, with the MAPE values of about 9% and 0.9%, respectively. Random Forest (RF) and EXtreme Gradient Boosting (XGBoost) regression were found to be the best algorithms for TN and TP effluent parameters, with the MAPE values of about 34% and 27%, respectively. Further, when the results were evaluated together according to all the performance metrics, RF, SVRM (with both linear kernel and RBF kernel), and Hybrid Regression algorithms generally made more successful predictions than Light GBM and XGBoost algorithms for all the parameters. Through this case study we demonstrated selective application of ML algorithms can be used to predict different effluent parameters more effectively. Wider implementation of this approach can potentially reduce the resource demands for active monitoring the environmental performance of WWTPs.

Poor communication by health care professionals may lead to life-threatening complications: examples from two case reports.

We report two cases which highlight the fact how poor communication leads to dangerously poor health outcome. We present the case of a 50-year-old woman recently diagnosed with rheumatoid arthritis from Southern Nepal presented to Patan hospital with multiple episodes of vomiting and oral ulcers following the intake of methotrexate every day for 11 days, who was managed in the intensive care unit. Similarly, we present a 40-year-old man with ileo-caecal tuberculosis who was prescribed with anti-tubercular therapy (ATT) and prednisolone, who failed to take ATT due to poor communication and presented to Patan Hospital with features of disseminated tuberculosis following intake of 2 weeks of prednisolone alone. These were events that could have been easily prevented with proper communication skills. Improvement of communication between doctors and patients is paramount so that life-threatening events like these could be avoided.

Impact evaluation of green-grey infrastructure interaction on built-space integrity: an emerging perspective to urban ecosystem service.

This paper evaluates the role of urban green infrastructure (GI) in maintaining integrity of built-space. The latter is considered as a lateral ecosystem function, worth including in future assessments of integrated ecosystem services. The basic tenet is that integrated green-grey infrastructures (GGIs) would have three influences on built-spaces: (i) reduced wind withering from flow deviation; (ii) reduced material corrosion/degeneration from pollution removal; and (iii) act as a biophysical buffer in altering the micro-climate. A case study is presented, combining the features of computational fluid dynamics (CFD) in micro-environmental modelling with the emerging science on interactions of GGIs. The coupled seasonal dynamics of the above three effects are assessed for two building materials (limestone and steel) using the following three scenarios: (i) business as usual (BAU), (ii) summer (REGEN-S), and (iii) winter (REGEN-W). Apparently, integrated ecosystem service from green-grey interaction, as scoped in this paper, has strong seasonal dependence. Compared to BAU our results suggest that REGEN-S leads to slight increment in limestone recession (<10%), mainly from exacerbation in ozone damage, while large reduction in steel recession (up to 37%) is observed. The selection of vegetation species, especially their bVOC emission potential and seasonal foliage profile, appears to play a vital role in determining the impact GI has on the integrity of the neighbouring built-up environment.

Systems scale assessment of the sustainability implications of emerging green initiatives.

This paper demonstrates a systems framework for assessment of environmental impacts from 'green initiatives', through a case study of meso-scale, anthropogenic-biogenic interactions. The following cross-sectoral green initiatives, combining the emerging trends in the North East region of the United Kingdom, have been considered - increasing the vegetation cover; decarbonising road transport; decentralising energy production through biomass plants. Two future scenarios are assessed - Baseline_2020 (projected emissions from realisation of policy instruments); Aggressive_2020 (additional emissions from realisation of green initiatives). Resulting trends from the Aggressive_2020 scenario suggest an increase in emissions of pollutant precursors, including biogenic volatile organic compounds and nitrogen dioxide over the base case by up to 20% and 5% respectively. This has implications for enhanced daytime ozone and secondary aerosols formation by up to 15% and over 5% respectively. Associated land cover changes show marginal decrease of ambient temperature but modest reductions in ammonia and ambient particulates.

Air flow and concentration fields at urban road intersections for improved understanding of personal exposure.

This paper reviews the state of knowledge on modelling air flow and concentration fields at road intersections. The first part covers the available literature from the past two decades on experimental (both field and wind tunnel) and modelling activities in order to provide insight into the physical basis of flow behaviour at a typical cross-street intersection. This is followed by a review of associated investigations of the impact of traffic-generated localised turbulence on the concentration fields due to emissions from vehicles. There is a discussion on the role of adequate characterisation of vehicle-induced turbulence in making predictions using hybrid models, combining the merits of conventional approaches with information obtained from more detailed modelling. This concludes that, despite advancements in computational techniques, there are crucial knowledge gaps affecting the parameterisations used in current models for individual exposure. This is specifically relevant to the growing impetus on walking and cycling activities on urban roads in the context of current drives for sustainable transport and healthy living. Due to inherently longer travel times involved during such trips, compared to automotive transport, pedestrians and cyclists are subjected to higher levels of exposure to emissions. Current modelling tools seem to under-predict this exposure because of limitations in their design and in the empirical parameters employed.

Estimation of age-related vulnerability to air pollution: assessment of respiratory health at local scale.

This paper demonstrates association of short-term variation in pollution and health outcomes within the same geographical area for a typical urban setting in the northern part of the UK from time series analysis. It utilises publicly available datasets for regulated air pollutants (PM10, NO2, SO2, CO and O3), meteorology and respiratory hospital admissions (and mortality) between April 2002 and December 2005 to estimate the respiratory health effect of pollution exposure, mainly in the elderly. Our results show that PM10 and O3 are positively associated with respiratory hospital admissions in the elderly, specifically in the age group 70-79. CO effects seem to be concentrated on the most elderly age group (80+) whereas NO2 seems to have the opposite age-related effect, with lower effects on the more elderly.

Mitigating secondary aerosol generation potentials from biofuel use in the energy sector.

This paper demonstrates secondary aerosol generation potential of biofuel use in the energy sector from the photochemical interactions of precursor gases on a life cycle basis. The paper is divided into two parts-first, employing life cycle analysis (LCA) to evaluate the extent of the problem for a typical biofuel based electricity production system using five baseline scenarios; second, proposing adequate mitigation options to minimise the secondary aerosol generation potential on a life cycle basis. The baseline scenarios cover representative technologies for 2010 utilising energy crop (miscanthus), short rotation coppiced chips and residual/waste wood in different proportions. The proposed mitigation options include three approaches-biomass gasification prior to combustion, delaying the harvest of biomass, and increasing the geographical distance between the biomass plant and the harvest site (by importing the biofuels). Preliminary results indicate that the baseline scenarios (assuming all the biomass is sourced locally) bear significant secondary aerosol formation potential on a life cycle basis from photochemical neutralisation of acidic emissions (hydrogen chloride and sulphur dioxide) with ammonia. Our results suggest that gasification of miscanthus biomass would provide the best option by minimising the acidic emissions from the combustion plant whereas the other two options of delaying the harvest or importing biofuels from elsewhere would only lead to marginal reduction in the life cycle aerosol loadings of the systems.

An integrated tool to assess the role of new planting in PM10 capture and the human health benefits: a case study in London.

The role of vegetation in mitigating the effects of PM(10) pollution has been highlighted as one potential benefit of urban greenspace. An integrated modelling approach is presented which utilises air dispersion (ADMS-Urban) and particulate interception (UFORE) to predict the PM(10) concentrations both before and after greenspace establishment, using a 10 x 10 km area of East London Green Grid (ELGG) as a case study. The corresponding health benefits, in terms of premature mortality and respiratory hospital admissions, as a result of the reduced exposure of the local population are also modelled. PM(10) capture from the scenario comprising 75% grassland, 20% sycamore maple (Acer pseudoplatanus L.) and 5% Douglas fir (Pseudotsuga menziesii (Mirb.) Franco) was estimated to be 90.41 t yr(-1), equating to 0.009 t ha(-1) yr(-1) over the whole study area. The human health modelling estimated that 2 deaths and 2 hospital admissions would be averted per year.

Measurements of atmospheric aerosol size distributions by co-located optical particle counters.

Ambient aerosol number concentrations and size distributions were measured in both indoor and outdoor environments using two identical co-located and concurrently operated optical particle counters (OPCs). Indoor measurements were performed in a research laboratory, whereas two different locations were used for outdoor measurements; the sampling duration exceeded 12 hours and one hour respectively. Results from the two OPCs have been presented for eight size classes between 0.5 and 20 [micro sign]m, represented by central value diameters 0.875, 1.5, 2.75, 4.25, 6.25, 8.75, 12.5 and 15 microm. Overall, for the six indoor and outdoor experiments conducted at different times of day, the mean particle count ratios from the two OPCs for the individual samples showed +/-20% variation for indoor experiments and +/-50% variations for outdoor experiments. Significant random departures of the mean ratios from unity at all size classes were noticed even for indoor sample periods exceeding 20 hours. However, the coefficient of determination (R(2)) for the plots of readings from the two OPCs indicated higher consistency for "fine" particles (0.5-3.5 microm) than for "coarse" particles (10-20 microm), with average R(2) > 0.8 and R(2) < 0.5 respectively. Poisson counting statistics help to explain the divergence in the latter case where number concentrations were very low for the outdoor experiments. However, it cannot explain the divergence for indoor measurements where the concentrations were much higher. Increasing the averaging period reduced the scatter, especially in size classes with low number concentration. However, this procedure may lead to over-smoothing of data for environments with rapidly changing number concentration. These results indicate that, when two such analysers are used for comparative studies, the divergence between their responses may generate significant values of source contribution or deposition flux, even for nominally similar aerosol populations.