Evaluating impacts of climate and management on reservoir water quality using environmental fluid dynamics code.

Climate change and human interference, notably nutrient input, affect the water quality. Nitrogen (N) and phosphorus (P) are pivotal in managing eutrophication. This study investigated the effects of water dynamics and chemical constituents on water quality in Hongfeng Lake, a typical weakly stratified reservoir suffering from algae blooms in Southwest China, using the Environmental Fluid Dynamics Code. Leveraging climate, hydrological, and water quality data, we constructed, calibrated, and validated the temperature-hydrodynamics-water quality-sediment model. Various scenarios were analyzed, including wind speed, air temperature, solar radiation, rainfall, water discharge, N and P external input, and internal release. The findings revealed that no rain and warming increased trophic state index (TSI) and chlorophyll-a (Chl-a) concentration, and no solar radiation initially elevated nitrate concentration, followed by an increase in ammonium concentration. Besides, no solar radiation and changes in rainfall significantly increased total phosphate concentration. The management scenarios of N and P reduction, halving tributary, and mainstream flow scenarios improved water quality and reduced eutrophication. The wind speed under the N and P reduced scenarios showed that a doubling in wind led to increased concentrations of the particulate organic matter, Chl-a, and dissolved oxygen, alongside decreased ammonium and nitrate, while TSI exhibited minimal change. However, 5- and 10-times wind speed scenarios amplified TSI in shallow water, potentially due to a substantial rise in internal nutrient release. The degradation trend observed in drinking water quality amid climate change (warming and flooding) raises concerns regarding health-related risks. These simulations provided the quantified influence of climate change and environmental management strategies on water quality in the weakly stratified reservoir, notably highlighting the looming threat of exacerbated eutrophication due to warming, necessitating more stringent N and P reduction measures compared to current practices.

Numerical study of the future PM2.5 concentration under climate change and best-health-effect (BHE) scenario.

The Beijing-Tianjin-Hebei (BTH) is one of the key areas with PM2.5 air pollution in China. Driven by the PM2.5 target accessibility of the Interim Target-1 (IT-1) by World Health Organization (WHO) and China's carbon neutrality, this study explored and quantified the contribution of climate change and anthropogenic emission to future PM2.5 in the region. The experiments considered future climate change scenarios RCP8.5, RCP4.5, and RCP2.6 with the baseline (Base) and reduced emission (EIT1) inventories in 2030, and RCP4.5 climate scenario with 3 emission inventories in 2050, the additional strong control emission scenario called Best-Health-Effect (BHE). Under various climate scenarios, the future air quality research modelling system projected annual PM2.5 concentrations nearing 35 µg/m3 in 2030. However, considering only the effect of emission reduction, the annual PM2.5 concentrations under EIT1 emission scenario is about 35% less than under Base scenario in different key years. The future PM2.5 concentrations are highly related to anthropogenic emission from human activities, while climate change by 2030 or 2050 has little impact on future air quality over the BTH region. The BHE emission reduction is significantly required for China to meet the new PM2.5 guideline value of WHO in the future.

Research on the connectivity of urban river network-wetland and water quality simulation.

The connectivity of urban river networks plays an important role in cities in many aspects, such as urban water safety, water quality (WQ), and aquatic ecological balance. This study focuses on the river network and the Majiawan Wetland in the Chaoyang District of Beijing by establishing a two-dimensional hydrological WQ model employing various water allocation schemes between the river network and the wetland. Water circulation and WQ are the main indexes, and the effects of different scenarios on improving water circulation and WQ are simulated and compared. This study demonstrates that the addition of water replenishment at the intersection of river network and internal slow-water zones of the wetland (Scheme 2) has greater effectiveness in improving both hydrology and WQ compared to two other schemes. The water area of the Majiawan Wetland has expanded, and water velocity has increased. Using chemical oxygen demand, total nitrogen, and total phosphorus as the index values for determining the water class, the WQ of about 20% of the wetland area was reached Water Class II (domestic drinking water), with Water Class III (general industrial water) accounting for the other 80%. This study provides valuable evaluation and reference for similar areas of urban river network connectivity.

[Differences of Three Methods in Determining Ozone Sensitivity in Nanjing].

In recent years， ozone （O3） has become an increasingly important air pollutant in China. Identifying the sensitivity of O3 to the precursors volatile organic compounds （VOCs） and nitrogen oxides （NOx） can help make effective abatement strategies. This study compared three methods for determining O3-VOCs-NOx sensitivity： simulated photochemical indicator values and sensitivity coefficients derived from a three-dimensional air quality model and an observation-based model （OBM）， with a case study involving an O3 pollution event that occurred in Nanjing in late July 2017. The results showed that O3 sensitivity based on the photochemical indicator and sensitivity coefficients demonstrated similar spatial variations （over 50% of the grid cells of Nanjing exhibiting identical O3 sensitivity）. However， sensitivity coefficients identified a larger number of areas within a transitional O3 sensitivity regime， as opposed to the VOCs- or NOx-limited regime identified by the photochemical indicator. The determination of the latter was affected by the adopted threshold values. The OBM relied on the quality of the observational data. For example， positive biases in observed NO2 could lead to an underestimation of O3 sensitivity to NOx with the OBM. During the high pollution period， the three methods exhibited significant disparities. The photochemical indicator tended to suggest the VOCs-limited condition， whereas the OBM and sensitivity coefficients indicated the NOx-limited or transitional regimes.

Hydrodynamics and phosphorus loading in an urbanized river channel influences response to future managed change: Insights from advection-dispersion modelling.

There is a need to understand what makes certain targeted measures for in-river phosphorus load reduction more effective than others. Therefore, this paper investigates multiple development scenarios in a small lowland polluted river draining an urban area (The Cut, Bracknell, UK), using an advection-dispersion model (ADModel-P). A comparative analysis is presented whereby changes in concentrations and fluxes of soluble reactive phosphorus (SRP) and organic phosphorus (OP) have been attributed to specific transformations (mineralization, sedimentation, resuspension, adsorption-desorption, and algal uptake) and correlated to controlling factors. Under present day conditions the river stretch is a net source of SRP (10.4 % increase in mean concentration) implying a release of previously accumulated material. Scenarios with the greatest impact are those based on managed reduction of phosphorus load in sources (e.g., 20 % increase in afforestation causes an in-river SRP and OP reduction of 1.3 % to 12.6 %) followed by scenarios involving changes in water temperature (e.g., 1 °C decrease leads to in-river SRP reduction around 3.1 %). Measures involving increased river residence time show the lowest effects (e.g., 16 % decrease in velocity results in under 0.02 % in-river SRP and OP reduction). For better understanding downstream persistence of phosphorus pollution and the effectiveness of mitigation measures the research demonstrates the importance of establishing when and where reaches are net adsorbers or desorbers, and whether sedimentation or resuspension is important.

North Korean CO emissions reconstruction using DMZ ground observations, TROPOMI space-borne data, and the CMAQ air quality model.

Emission uncertainty in North Korea can act as an obstacle when developing air pollution management plans in the country and neighboring countries when the transboundary transport of air pollutants is considered. This study introduces a novel approach for adjusting and reallocating North Korean CO emissions, aiming to complement the limited observational and emissions data on the country's air pollutants. We utilized ground observations from demilitarized zone (DMZ) and vertical column density (VCD) data from a TROPOspheric Monitoring Instrument (TROPOMI), which were combined with the Community Multi-Scale Air Quality (CMAQ) chemistry transport model simulations. The Clean Air Support System (CAPSS) and Satellite Integrated Joint Monitoring of Air Quality (SIJAQ) emissions inventories served as the basis for our initial simulations. A two-step procedure was proposed to adjust both the emission intensity and the spatial distribution of emissions. First, air quality simulations were conducted to explore model sensitivity to changes in North Korean CO emissions with respect to ground concentrations. DMZ observations then constrained these simulations to estimate corresponding emission intensity. Second, the spatial structure of North Korean CO emission sources was reconstructed with the help of TROPOMI CO VCD distributions. Our two-step hybrid method outperformed individual emissions adjustment and spatial reallocation based solely on surface or satellite observations. Validation using ground observations from the Chinese Dandong site near the China-North Korea border revealed significantly improved model simulations when applying the updated CO emissions. The adjusted CO emissions were 10.9 times higher than those derived from the bottom-up emissions used in this study, highlighting the lack of information on North Korean pollutants and emission sources. This approach offers an efficient and practical solution for identifying potential missing emission sources when there is limited on-site information about air quality on emissions.

[Variation Characteristics of PM2.5 Pollution and Transport in Typical Transport Channel Cities in Winter].

Taking Handan, Xingtai, Hengshui, and Cangzhou, four cities in southwest Hebei Province along the Beijing-Tianjin-Hebei typical transport route, as examples, we analyzed the variation characteristics of 3a meteorological conditions and PM2.5 concentration in winter from 2019 to 2021 and used potential source contribution analysis (PSCF) and concentration weight analysis (CWT) to identify the transport characteristics of PM2.5 in the four cities during the study period. Based on the meteorological air quality model (WRF-CMAQ) transmission matrix method and transport flux method, the contribution of PM2.5 transport between Handan, Xingtai, Hengshui, and Cangzhou and the surrounding areas was quantitatively assessed; the vertical distribution characteristics of PM2.5 net transport flux were revealed; and the two main transport routes of PM2.5 pollution were further identified. The results showed that during the study period, the PM2.5 concentration decreased by 45.85%, 49.45%, 42.40%, and 31.65%, respectively. The potential source contribution of Handan and Xingtai was mainly distributed in south-central Shanxi (Linfen, Changzhi, and Jinzhong), northern Henan (Xinxiang, Kaifeng, and Zhengzhou), and a small part of Inner Mongolia (PSCF > 0.9). The potential contribution areas of Hengshui and Cangzhou were mainly concentrated in southern Hebei (Handan and Shijiazhuang), central Shanxi (Taiyuan and Yangquan), and some Shandong regions (PSCF > 0.7), and the CWT results were similar to those of PSCF. During the study period, the local contribution (51.11%-62.99%) was slightly higher than the regional contribution (37.01%-48.89%) during winter in the four cities. Affected by horizontal turbulence and vertical diffusion, the impact of regional transmission in 2020 was slightly higher than that in other years (0.50%-9.52%). In 2021, the influence of regional transmission was slightly lower than that of other years (-2.15%--9.52%) due to low PM2.5 concentration and meteorological factors. For Handan, Xingtai, Hengshui, and Cangzhou, the total inflow (outflow) flux intensity of the four cities during winter and the surrounding areas was in 2020 > 2021 > 2019. For the total net flux, the total inflow (outflow) flux intensity of the four cities in winter was 0.094, -0.070, and 0.087 kt·d-1 (Xingtai:0.212, 0.395, and 0.544 kt·d-1; Hengshui:-0.040, -0.228, and 0.185 kt·d-1; Cangzhou:0.062, 0.126, and 0.128 kt·d-1). During the study, Handan, Xingtai, and Cangzhou were mostly used as transport receptors, whereas Hengshui was mostly used as a transport source. In the range of 0-1 260 m, the net transport flux intensity of PM2.5 increased basically with the increase in height, and the maximum net flux of the various cities in different periods was different. The maximum net flux of Handan, Xingtai, and Hengshui was 252-1 261 m, 817 m, and 252-817 m, respectively. The maximum net flux in Cangzhou was 252-359 m. By analyzing the transmission characteristics of the four cities, it was found that there were two main transport directions of PM2.5, that is, the northwest-southeast direction (Shanxi → Handan → Henan and Shandong; Shijiazhuang → Xingtai → Handan and Shandong; Baoding → Cangzhou → Shandong) and the southwest-northeast direction (Shanxi → Xingtai → Hengshui → Cangzhou → Bohai Bay).

Engaging healthcare professionals and patient representatives in the development of a quality model for hospitals: a mixed-method study.

Top-down and externally imposed quality requirements can lead to improvement but do not seem as sustainable as intended. There is a need for a quality model that intrinsically motivates healthcare professionals to contribute to quality and safe care in hospitals. This study shows how a quality model that matches the identity and the quality vision of the organization was developed. A multimethod design with three phases was used in the development of the model at a large teaching hospital in Belgium. In the first phase, 14 focus groups and 19 interviews with staff members were conducted to obtain an overview of the quality and safety challenges, complemented by a plenary discussion with the members of the patient advisory council. In the second phase, the challenges that had been captured were further assessed using a hospital-wide survey for all hospital staff. Finally, a newly established quality review board (with internal and external stakeholders) critically evaluated the input of Phases 1 and 2 and defined the basic quality standards to be implemented in the hospital. A first evaluation 2 years after the implementation was conducted based on (i) patients' perceptions of quality of care and patient safety by publicly available indicators collected in 2016, 2019, and 2022 and (ii) staff experiences and perceptions regarding the acceptability of the new model gathered through (grouped) interviews and an open questionnaire. The quality model consists of eight broad themes, including norms for the hospital staff (n = 27), sustained with quality systems (n = 8), and organizational support (n = 6), with aid from adequate management and leadership (n = 6). The themes were converted into 46 standards. These should be supported within a safe, efficient, and caring work environment. The new model was launched in the hospital in June 2021. The evaluation shows a significant difference in quality and safety on different dimensions as perceived by hospitalized patients. The perceived added value of the participatory model is a better fit with the needs of employees and the fact that the model can be adjusted to the specific context of the different hospital departments. The lack of hard indicators is seen as a challenge in monitoring quality and safety. The participation of various stakeholders inside and outside the organization in defining the quality challenges resulted in the creation of a participatory quality model for the hospital, which leads towards a better-supported quality policy in the hospital.

AI-based prediction of the improvement in air quality induced by emergency measures.

Several cities in the developing world, of which the capital city of India, New Delhi, is an example, often experience air quality in which pollutant levels go way above the levels considered hazardous for human health. To bring down the air quality to within permissible limits quickly, the measures typically taken involve shutting down certain high-polluting activities for some time to enable the air quality to recover temporarily. This paper presents a first-ever model based on artificial neural networks to forecast the extent of reduction in air quality parameters that can be achieved and the time period within which a change can be experienced when the source of the emissions is cut off temporarily. The model is based on the extensive data on the extent of reduction in air quality parameters that occurred during the lockdown that was imposed during the COVID-19 pandemic. The non-linear autoregressive exogenous network-based model chosen for the purpose employs the hour since stopping of emissions, relative humidity, wind speed, wind direction, and ambient temperature as input parameters to predict the rate of change of PM2.5 with respect to the concentration at the start of the stopping of the emissions. Air quality data from a key monitoring station in New Delhi was used to develop the model. The model predicted the rate of drop in PM2.5 with an R and MSE of 0.0044 and 0.9736, respectively, while training and 0.0095 and 0.9583 while testing. The model was then tested with data from 19 other stations in New Delhi, and accuracy of the model was found to be exceptionally accurate, with the correlation between the measured and the predicted PM2.5 levels ranging from 0.74 to 0.94 and the MSE ranging from 0.0110 to 1.0746. Thus, the model can be employed to determine the number of hours of temporary stoppage of emissions required for the PM2.5 concentration to reach safe levels. The methodology of development of the model can be extrapolated to construct models tailored for use in other parts of the world as well.

Evaluation of clinical practice guideline-derived clinical decision support systems using a novel quality model.

Over the last decade, clinical practice guidelines (CPGs) have become an important asset for daily life in healthcare organizations. Efficient management and digitization of CPGs help achieve organizational objectives and improve patient care and healthcare quality by reducing variability. However, digitizing CPGs is a difficult, complex task because they are usually expressed as text, and this often leads to the development of partial software solutions. At present, different research proposals and CPG-derived CDSS (clinical decision support system) do exist for managing CPG digitalization lifecycles (from modeling to deployment and execution), but they do not all provide full lifecycle support, making it more difficult to choose solutions or proposals that fully meet the needs of a healthcare organization. This paper proposes a method based on quality models to uniformly compare and evaluate technological tools, providing a rigorous method that uses qualitative and quantitative analysis of technological aspects. In addition, this paper also presents how this method has been instantiated to evaluate and compare CPG-derived CDSS by highlighting each phase of the CPG digitization lifecycle. Finally, discussion and analysis of currently available tools are presented, identifying gaps and limitations.

Unveiling the importance of VOCs from pesticides applicated in main crops for elevating ozone concentrations in China.

Volatile organic compounds (VOCs) are considered as important precursors of ozone in the air, while the contribution of VOCs from pesticide application (PVOCs) to ozone production is unknown. Utilizing data from the Ministry of Agriculture and Rural Affairs of the People's Republic of China and ChinaCropPhen1km, this paper developed PVOC emission inventories with a resolution of 1 km for the main crops (rice, maize, and wheat) from 2012 to 2019 in China. The results revealed that pesticide application is an important VOC emission source in China. Specially, the PVOC emissions from the major grain-producing regions in June accounted for approximately 30% of the annual total PVOC emissions in the local regions. The simulation with the Weather Research and Forecasting Community Multiscale Air Quality model (WRF-CMAQ) indicated that the PVOC emissions increased the mean maximum daily 8-hour average (MDA8) ozone concentration across China by 2.5 ppb in June 2019. During the same period, PVOCs in the parts of North China Plain contributed 10% of the ozone formation. Under the comprehensive emission reduction scenario, it is anticipated that by 2025, the joint implementation of measures including reducing pesticide application, improving pesticide utilization efficiency and promoting solvent substitution will decrease PVOC emissions by 60% compared with 2019, thereby mitigating ozone pollution.

Evolution of Ozone Formation Sensitivity during a Persistent Regional Ozone Episode in Northeastern China and Its Implication for a Control Strategy.

In recent years, the magnitude and frequency of regional ozone (O3) episodes have increased in China. We combined ground-based measurements, observation-based model (OBM), and the Weather Research and Forecasting and Community Multiscale Air Quality (WRF-CMAQ) model to analyze a typical persistent O3 episode that occurred across 88 cities in northeastern China during June 19-30, 2021. The meteorological conditions, particularly the wind convergence centers, played crucial roles in the evolution of O3 pollution. Daily analysis of the O3 formation sensitivity showed that O3 formation was in the volatile organic compound (VOC)-limited or transitional regime at the onset of the pollution episode in 92% of the cities. Conversely, it tended to be or eventually became a NOx-limited regime as the episode progressed in the most polluted cities. Based on the emission-reduction scenario simulations, mitigation of the regional O3 pollution was found to be most effective through a phased control strategy, namely, reduction of a high ratio of VOCs to NOx at the onset of the pollution and lower ratio during evolution of the O3 episode. This study presents a new possibility for regional O3 pollution abatement in China based on a reasonable combination of OBM and the WRF-CMAQ model.

Integrating impacts of climate change on aquatic environments in inter-basin water regulation: Establishing a critical threshold for best management practices.

Inter-basin water diversion (IBWD) is a viable strategy to tackle water scarcity and quality degradation due to climate change and increasing water demand in headwaters regions. Nevertheless, the capacity of IBWD to mitigate the impacts of climate change on water quality has rarely been quantified, and the underlying processes are not well understood. Therefore, this study aims to elucidate how the IBWD manipulated total phosphorus (TP) loading dilution and conveying patterns under climate change and determine a critical threshold for the quantity of water entering downstream reservoirs (WIN) for operational scheduling. To resolve this issue, climate-driven hydrologic variability over a 60-year period was derived utilizing the least square fitting approach. Subsequently, six scenarios evaluating the response of in-lake TP concentrations (TPL) to increased temperatures and IBWDs of 50 %, 100 %, and 150 % from the baseline water volume in 2030 and 2050 were studied by employing a calibrated hydrological-water quality model (SWAT-YRWQM). In the next stage, three datasets derived from mathematical statistics based on the observed data, the Vollenweider formula, and modeled projections were integrated to formulate best management practices. The results revealed that elevated air temperatures would lead to reduced annual catchment runoff but increased IBWD. Additionally, our study quantified the IBWD potential for mitigating water quality degradation, indicating the adverse effects of climate change on TPL would be weakened by 4.2-14.4 %. A critical threshold for WIN was also quantified at 617 million m3, maintaining WIN at or near 617 million m3 through optimized operational scheduling of IBWD could effectively restrict external inflow TP loading to lower levels. This study clearly illustrates the intricate interactive effects of climate change and IBWD on aquatic environments. The methodology elucidated in this study for determining the critical threshold of WIN could be applied in water management for analogous watershed-receiving waterbody systems.

Bayesian-based calibration for water quality model parameters.

To improve the efficiency and accuracy of water quality model parameter calibration and avoid local optima and the phenomenon in which different parameters have the same effect, this paper proposed a novel Bayesian-based water quality model parameter calibration method. Using Bayesian inference, the parameter calibration problem was converted into a posterior probability function sampling problem, which was sampled using the Markov Chain Monte Carlo algorithm. The convergence speed of the calibration was further improved by setting the optimized initial sampling value. The influences of the initial sampling value, Markov chain length, and proposal distribution form on the calibration effect were evaluated using four specific cases. The results indicate that (1) the mean relative error (MRE) of the parameter calibration results of this method is less than 10%, with the calibration MRE of Dx and Dy being 5.3% and 8.3%, respectively; (2) when the parameter sensitivity is low, the calibration effect of this method is relatively poor, with a calibration MRE of 46% for k; (3) the parameter calibration can be completed more efficiently by setting an optimized initial value for the MCMC, choosing a reasonable Markov chain length and a suitable proposal distribution form. PRACTITIONER POINTS: Bayesian-based water quality model parameter calibration method is proposed and posterior probability distribution was sampled using the MCMC algorithm. Parameter calibration can be completed more efficiently by setting an optimized initial value for the MCMC. As a result, efficient and accurate parameter calibration of water quality models was achieved. This method is widely applicable to various models, and the calibration speed depends on the calculation speed of the model.

Health effects of future dioxins emission mitigation from Chinese municipal solid waste incinerators.

Dioxins (including 2,3,7,8-tetrachlorodibenzo-p-dioxin, as Group 1 Carcinogen) in the atmosphere mainly originate from incomplete combustion during municipal solid waste (MSW) incineration. To significantly reduce dioxins emission from the MSW incineration industry, China has promulgated a set of ambitious plans regulating MSW-related pollution; however, the emission reduction potentials and concomitant environmental and health impacts associated with the implementation of these programs on a national scale remain unknown. Here, we use real measurements from official environmental impact assessment systems and continuous emissions monitoring systems (covering 96.6% of national MSW incinerators) to estimate unit-level dioxins emission and concomitant environmental and health impacts. We find that in 2018, 99.3% and 66.7% of Chinese incinerators met such concentration and temperature standards, respectively, controlling the total emissions to 19.6 g toxic equivalency quantity and maintaining carcinogenic and noncarcinogenic risks significantly below safety levels nationwide. Fully achieving both current standards and future regulations will reduce emissions and health risks by 67.7% and 62.6%, respectively, with waste sorting program contributing the majority. This study reveals substantial benefits from curbing MSW-related dioxins pollution and underscores the promise of ongoing management.

Framework of wind joint analysis for different lake regions and its effects on the water quality.

Water quality of Lake Taihu (LT) is paid wide attention, and the wind field makes wind-induced flow, significantly impacting the water quality. As a wide lake, the wind field suffers spatial and temporal changes. The correlated relationship among the wind fields for different lake regions has not been studied, and the joint effects of wind field on the water quality is still unknown. Hence, this paper proposed a framework of wind joint analysis for different lake regions and modelling its effects on the water quality, including joint analysis of wind field for different lake regions using Copula function, random time series generation of wind field using Monte-Carlo simulation, and hydrodynamic and water quality numerical simulation. Taking the Lake Taihu (LT) as study case, the joint relationships of wind field for four lake regions were analyzed, and the CODMN, TP and TN distributions under different wind fields were simulated. This paper showed the following: (1) The relationship between the wind speed and direction was weak, and the correlated relationships among the wind fields for four lake regions were significant (ρ > 0.5). (2) The water quality of LT was more influenced by the wind direction rather than the wind speed, with an impacting ratio of ∼4.5. (3) The discharged weighted angle of runoff outflow (DWARO) was a practical index to improve the water quality. When regulating the input/output runoff discharge, water diversion project and water intakes in practice, the administrations should make the DWARO less than or equal to the average wind direction, to decrease the average pollutant concentration and improve the water quality of lake and intake. The proposed framework and results of LT could be extended to other wide shallow lakes to support the environmental management and basin runoff regulation.

Insights into the transport and bio-degradation of dissolved inorganic nitrogen in the biochar-pyrite amended stormwater biofilter using dynamic modeling.

The stormwater biofilter is a prevailing green infrastructure for urban stormwater management, but it is less effective in dissolved nitrogen removal, especially for nitrate. The mechanism that governs the nitrate leaching and performance stability of stormwater biofilters is poorly understood. In this study, a water quality model was developed to predict the ammonium and nitrate dynamics in a biochar-pyrite amended stormwater biofilter. The transport of dissolved nitrogen species was described by advection-dispersion models. The kinetics of adsorption and pyrite-based autotrophic denitrification are included in the model and simulated with a steady-state saturated flow. The model was calibrated and validated using eleven storm events. The modeling results reveal that the contribution of pyrite-based autotrophic denitrification to nitrate leaching alleviation improves with the increased drying duration. The nitrate removal efficiency was affected by a series of design parameters. Pyrite filling rate has a minor effect on nitrate removal promotion. Service area ratio and submerged zone depth are the key parameters to prevent nitrate leaching, as they influence the emergence and discharge time of nitrate breakthrough. The high inflow volume (high service area ratio) and small submerged zone can lead to earlier and increased discharge of peak nitrate otherwise the peak nitrate could be retained in the submerged zone and denitrified during the drying period. The developed mechanistic model provides a useful tool to evaluate the treatment ability of stormwater biofilters under varying conditions and offers a guideline for biofilter design optimization.

Low-Cost Particulate Matter Sensors for Monitoring Residential Wood Burning.

Conventional monitoring systems for air quality, such as reference stations, provide reliable pollution data in urban settings but only at relatively low spatial density. This study explores the potential of low-cost sensor systems (LCSs) deployed at homes of residents to enhance the monitoring of urban air pollution caused by residential wood burning. We established a network of 28 Airly (Airly-GSM-1, SP. Z o.o., Poland) LCSs in Kristiansand, Norway, over two winters (2021-2022). To assess performance, a gravimetric Kleinfiltergerät measured the fine particle mass concentration (PM2.5) in the garden of one participant's house for 4 weeks. Results showed a sensor-to-reference correlation equal to 0.86 for raw PM2.5 measurements at daily resolution (bias/RMSE: 9.45/11.65 µg m-3). High-resolution air quality maps at a 100 m resolution were produced by combining the output of an air quality model (uEMEP) using data assimilation techniques with the network data that were corrected and calibrated by using a proposed five-step network data processing scheme. Leave-one-out cross-validation demonstrated that data assimilation reduced the model's RMSE, MAE, and bias by 44-56, 38-48, and 41-52%, respectively.

Comparison between the WFD approaches and newly developed water quality model for monitoring transitional and coastal water quality in Northern Ireland.

This study aims to evaluate existing approaches for monitoring and assessing water quality in waterbodies in the North of Ireland using newly developed methodologies. The results reveal significant differences between the new technique and the existing "one-out, all-out" approach in rating water quality. The new approach found the water quality status to be "good," "fair," and "marginal," whereas the existing "one-out, all-out" technique classified water quality as "good," and "moderate," respectively. The new technique outperformed existing approaches in rating the water quality of different waterbody types, with high R2 = 1, NSE = 0.99, and MEF = 0 values. Furthermore, the final assessment of water quality using the new methodologies had the lowest uncertainty (<1 %), whereas the efficiency measures (NSE and MEF) indicate that the new approaches are bias-free to assess water quality at any geographic scale. The results of this study reveal that the newly proposed methodologies are effective in assessing the water quality states of transitional and coastal waterbodies in the North of Ireland. The study also highlighted the limitations of existing approaches and the importance of updating water resource management systems for better protection of these waterbodies. The findings have significant implications for water resource management and planning in the North of Ireland and other similar regions.

Adjusting elemental carbon emissions in Northeast Asia using observed surface concentrations of downwind area and simulated contributions.

In this study, we developed a practical approach to augment elemental carbon (EC) emissions to improve the reproducibility of the most recent air quality with photochemical grid modeling in support of source-receptor relationship analysis. We demonstrated the usefulness of this approach with a series of simulations for EC concentrations over Northeast Asia during the 2016 Korea-United States Air Quality study. Considering the difficulty of acquiring EC observational data in foreign countries, our approach takes two steps: (1) augmenting upwind EC emissions based on simulated upwind contributions and observational data at a downwind EC monitor considered as the most representative monitor for upwind influences and (2) adjusting downwind EC emissions based on simulated downwind contributions, including the effects of updated upwind emissions from the first step and observational data at the downwind EC monitors. The emission adjustment approach resulted in EC emissions 2.5 times higher than the original emissions in the modeling domain. The EC concentration in the downwind area was observed to be 1.0 µg m-3 during the study period, while the simulated EC concentration was 0.5 µg m-3 before the emission adjustment. After the adjustment, the normalized mean error of the daily mean EC concentration decreased from 48 % to 22 % at ground monitor locations. We found that the EC simulation results were improved at high altitudes, and the contribution of the upwind areas was greater than that of the downwind areas for EC concentrations downwind with or without emission adjustment. This implies that collaborating with upwind regions is essential to alleviate high EC concentrations in downwind areas. The developed emission adjustment approach can be used for any upwind or downwind area when transboundary air pollution mitigation is needed because it provides better reproducibility of the most recent air quality through modeling with improved emission data.