Air Pollution Risk Assessment Research Articles

Risk assessment and prevention of air pollution to protect citizen health based on statistical data: a case study of Zhengzhou, China

Risk assessment and prevention of air pollution to protect citizen health based on statistical data: a case study of Zhengzhou, China

Human Health Risk Assessment of Air Pollution in the Regions of Unsustainable Heating Sources. Case Study—The Tourist Areas of Southern Poland

Air pollution is one of the main factors affecting human health. Air quality is especially important in the tourist areas developed with facilities for outdoor activities. During the winter season of 2017/2018, the concentrations of particulate matter (PM10, PM2.5, PM1), CO, O3, and NO2 were studied in 12 attractive tourist villages in the surroundings of the Czorsztyn Reservoir in southern Poland. Air pollutant measurements were performed continuously, using a single ground-based Alphasense air sensor. Our assessment of human health risk (HHRA), arising from inhalation exposure to air contaminants, was calculated for both local inhabitants and tourists, based on actual measured values. It was found that pollutant concentrations exceeded both permissible and recommended levels of PM10 and PM2.5. The mean total noncarcinogenic risk values were equal to 9.58 (unitless) for adults and 9.68 (unitless) for children and infants, under the resident exposure scenario. However, under the tourist exposure scenario, the mean total risk was equal to 1.63 (unitless) for adults and 1.64 (unitless) for children and infants. The risk to tourists was lower than that to inhabitants due to shorter exposure times. The target non-carcinogenic value of 1, calculated for PM10, PM2.5, and NO2, was significantly exceeded in total risk, under the residential exposure scenario, in reference to all the local subpopulations. In the majority of the investigated locations, the total risk exceeded the value of 1, under the tourist scenario, for all the subpopulations analysed. PM2.5 was recognised to be the most important contaminant in our risk analysis, in view of its share in the total risk value.

Concentration Analysis and Health Risk Assessment of Air Pollutants in Newly Decorated Public Places in Xi'an

In order to understand the levels of indoor air pollution and health risks in public places, our research group conducted air quality monitoring and human health risk assessments for five types of public places (offices, classrooms, laboratories, banks, and hospitals) in Xi'an City from December 2017 to July 2020. The test items included formaldehyde, benzene, toluene, xylene, n-butyl acetate, ethylbenzene, styrene, n-undecane, and total volatile organic compounds (TVOC). The results showed that formaldehyde had the highest exceedance rate (59.4%), followed by toluene, TVOC, benzene, and xylene. Among the five types of public places, hospitals had the highest rate of pollutants exceeding the standard (46.7%), and the main pollutants exceeding the standard were formaldehyde, benzene, and toluene. The results showed that the concentrations of formaldehyde and TVOC were positively correlated with temperature and humidity. The health risk assessment results showed that there were carcinogenic risks of formaldehyde and benzene in different places; people working in banks had a higher risk of formaldehyde carcinogenesis, and those working in hospitals had a higher risk of benzene carcinogenesis. This study provides a reference for the level of indoor air pollution in public places in Xi'an City, and is of great significance to the health risk research of related populations.

Long-Term Effects of Fine Particles on Mortality: Insights from 1984.

I review an important study that Professor Evans published early in his career examining the role of cross-sectional mortality studies in air pollution risk assessment. At a time when both risk assessment and particle effects on mortality were controversial, John's thoughtful analysis of the issues and data relevant to assessing long-term mortality risks from airborne particles provides a comprehensive primer that is still relevant today. The paper includes a critical literature review, a meta-analysis of published particle effect estimates, and a reanalysis of landmark cross-sectional mortality data set. EPA criteria documents and related literature had largely discounted the cross-sectional mortality findings on the basis of criticisms about exposure assessment and control for confounding. John's analysis reached a different conclusion, that is, "we are of the opinion that the cross-sectional studies reflect a causal relationship between exposure to airborne particles and premature mortality. From our point of view it is as likely that parameters have been underestimated … as that they are overestimated due to confounding." The paper acknowledged the impossibility of precisely quantifying the long-term mortality effect of particle air pollution, and that there is a need for further research utilizing alternative approaches. These conclusions foreshadow the emergence, a decade later, of the influential particulate matter (PM) mortality findings from the Harvard Six Cities and American Cancer Society cohort studies. I conclude by suggesting that well designed cross-sectional studies could play a role in identifying exposure-response associations in resource-poor settings where there is a paucity of local evidence to support air pollution regulations.

Air pollution and health risk assessment in Northeastern China: A case study of Jilin Province

In recent years, the pollution of the air environment has been increasing, which has seriously endangered human health. The large amount of coal burning and automobile exhaust emissions in winter have caused serious regional pollution, which has greatly increased the prevalence of respiratory disease of people. The purpose of this study is to use Jilin Province as an example to map out the environmental pollution status in Northeastern China, and to provide suggestions for the improvement of the atmospheric environment. Using the annual data of China's atmospheric monitoring, the atmospheric environment in Jilin was comprehensively analysed using ArcGIS, principal component analysis (PCA) and non-carcinogenic risk model calculations. The results showed that the temporal distribution of pollutants was winter > spring > autumn > summer, and the spatial distribution is decreasing from northwest to southeast. The PCA showed that the first principal components were PM2.5 and CO, and the second principal components were PM10 and O3. The main sources of air pollution were coal-fired (62.365%) and automobile emissions (19.153%). The non-carcinogenic risks of pollutants are all within the acceptable range (1 × 10−6), but as age increases, the risk gradually decreases, and the risk value of male is higher than that of female.

First Technical Specifications for Health Risk Assessment of Ambient Air Pollution in China.

First Technical Specifications for Health Risk Assessment of Ambient Air Pollution in China.

Risk Assessment of Ambient Air Pollutants and Health Impact around Fuel Stations in Urban Cities of KSA.

Background:In Saudi Arabia, fuel dispensing facilities commonly present around the residential places, educational institutions, and various health care facilities. Fuel pollutants such as benzene, toluene, and xylenes (BTX) and its alkyl derivatives are harmful to human health because of their toxic, mutagenic, or carcinogenic properties. The aim of this study was to determine the BTX concentration levels of common pollutants in and around fuel stations and their harmful health effects in the urban cites of KSA.Methods:Forty fuel dispensing facilities were randomly selected on the basis of three different areas: residential, traffic intersection, and petrol pump locations (refueling stations). Portable ambient analyzer was used for measuring BTX concentration. t-test was applied to determine the difference between these different areas.Results:All mean concentration values of pollutants such as BTX around residential, traffic intersection, and fuel stations are exceeding the limits of air quality standards values (P < 0.01). The mean levels of benzene are 10.3 and 11.07 ppm in Dammam and Khobar, respectively, and they exceed the reference level of 0.5 ppm. Hazard quotient was more than >1, which shows that carcinogenic probability has increased those who were living and working near fuel stations.Conclusions:The results found that the high concentration of pollutants (BTX) is in the environment around fuel stations. The environmental contamination associated with BTX in petrol fuel stations impulses the necessity of preventive programs to reduce the further air quality deterioration and reduce the harmful health effects.

High spatial resolution WRF-Chem model over Asia: Physics and chemistry evaluation

The representation of air quality and meteorology over Asia remains challenging for chemical transport models as a result of the complex interactions between the East Asian monsoons and the large uncertainty (in space and time) of the high anthropogenic emissions levels over the region. High spatial resolution models allow resolving small-scale features induced by the complex topography of this region. In this study, the Weather Research and Forecasting model with Chemistry (WRF-Chem) was used to simulate the spatial and seasonal variability of main physical and chemical variables over Asia for the year 2015 at 8-km horizontal resolution to enable resolving small-scale features induced by the region complex topography. The simulated atmospheric composition was evaluated against satellite retrievals (MOPITT, IASI + GOME2, MODIS and OMI) in addition to ground-based observations in China for the year 2015, while the meteorological variables were evaluated by several observational-based datasets (ERA5, CRU, MODIS, MTE). Results showed low to moderate seasonal biases for major meteorological variables, i.e. air temperature, relative humidity, precipitation, latent heat, sensible heat and snow cover fraction. Overall, WRF-Chem reproduced well the spatial and seasonal variability of lowermost tropospheric ozone content, total column carbon monoxide and aerosol optical depth, while large discrepancies were found for tropospheric nitrogen dioxide content, mainly during the warm season. In consistency with previous studies, the different biases between model-simulated and satellite-retrieved values can be mainly attributed to i) the large uncertainties in anthropogenic and natural nitrogen oxides emission estimates, as well as dust and sea salt emissions in the case of aerosol optical depth, and ii) some coarse parameterizations used to reproduce main small-scale features (e.g. meteorology, chemical processes, dry deposition to vegetation). Compared to ground-based observations, the WRF-Chem model reproduced well the mean annual cycle of surface nitrogen dioxide, ozone and fine particles concentrations in all seasons across China. Our results suggest that WRF-Chem provides reliable spatio-temporal patterns for most of the meteorological and chemical variables, adding thus confidence to its applicability in the context of air pollution risk assessment to human and ecosystems health.

In Vitro to ex Vivo/In Vivo Correlation (IVIVC) of dissolution kinetics from inhaled particulate solutes using air/blood barrier models: Relation between in vitro design, lung physiology and kinetic output of models

Correlating data from in vitro dissolution testing of inhaled particulate pharmaceuticals or air pollutants with the dissolution and distribution to the blood circulation of the same aerosols following inhalation in vivo is a major challenge. Better methods could benefit both inhaled drug development and the risk assessment of air pollutants. Five properties known to influence the results produced by in vitro methods are the particle deposition pattern, barrier thickness, surfactant distribution, perfusion strategy and distribution volume of dissolution. The purpose with this manuscript was to compare the rates of dissolution- and absorption of two particulate solutes, nicotine and Fluticasone Propionate (FP), in the Isolated, ventilated, and Perfused Lung of the rat (IPL) with that of non-biological test barriers simulating the same process in vitro. Three published test model barriers were compared; the DissolvIt with a mucous gel simulant and data for two other models, utilizing particle deposition on glass fiber filters; one Paddle over Disk model, and one Modified Transwell model. The more water-soluble nicotine, only tested in the ex vivo IPL and the in vitro DissolvIt model, had a very rapid first absorption half-time in both the IPL and the DissolvIt of respectively 1.9 and 0.55 min. For more lipophilic FP (Flixotide, MDI) the correlation of dissolution- and absorption data was compared for the inhaler formulation between the ex vivo rat IPL and all three in vitro test models. The results varied substantially between the in vitro models regarding simulated appearance in the blood circulation and, thus, regarding correlation with the ex vivo IPL model. The first half-time of in vitro dissolution- and absorption of FP to perfusate when normalized to the 8.6 h half-time measured for FP in the ex vivo IPL ranked as; 2.9, 0.021, and 0.17 for respectively the DissolvIt, the Paddle over Disk model, and the Modified Transwell model. Despite similar physicochemical properties of the solvents involved in all three in vitro models, it seems like resemblance of the models with the in vivo physiology has a profound influence on the dissolution- and absorption data produced.

Risk assessment of temperature and air pollutants on hospitalizations for mental and behavioral disorders in Curitiba, Brazil

BackgroundExtreme ambient temperatures and air quality have been directly associated with various human diseases from several studies around the world. However, few analyses involving the association of these environmental circumstances with mental and behavioral disorders (MBD) have been carried out, especially in developing countries such as Brazil.MethodsA time series study was carried out to explore the associations between daily air pollutants (SO2, NO2, O3, and PM10) concentrations and meteorological variables (temperature and relative humidity) on hospital admissions for mental and behavioral disorders for Curitiba, Brazil. Daily hospital admissions from 2010 to 2016 were analyzed by a semi-parametric generalized additive model (GAM) combined with a distributed lag non-linear model (DLNM).ResultsSignificant associations between environmental conditions (10 μg/m3 increase in air pollutants and temperature °C) and hospitalizations by MBD were found. Air temperature was the environmental variable with the highest relative risk (RR) at 0-day lag for all ages and sexes analyzed, with RR values of 1.0182 (95% CI: 1.0009–1.0357) for men, and 1.0407 (95% CI: 1.0230–1.0587) for women. Ozone exposure was a risk for all women groups, being higher for the young group, with a RR of 1.0319 (95% CI: 1.0165–1.0483). Elderly from both sexes were more susceptible to temperature variability, with a RR of 1.0651 (95% CI: 1.0213–1.1117) for women, and 1.0215 (95% CI: 1.0195–1.0716) for men.ConclusionsThis study suggests that temperatures above and below the thermal comfort threshold, in addition to high concentrations of air pollutants, present significant risks on hospitalizations by MBD; besides, there are physiological and age differences resulting from the effect of this exposure.Graphical abstract

Multi hours ahead prediction of surface ozone gas concentration: Robust artificial intelligence approach

Forecasting the Ozone concentration is a substantial process in many important environmental issues such air pollution management, risk assessment, public health, and global warming. Early and accurate prediction of Ozone is very significant for efficient monitoring of pollution towards constituting advanced early alarm systems. In this study, wavelet transform (WT) approach was applied to handle input variables prior to introduce them to artificial neural network (ANN). This approach attempts to remove the noise impacts which decreases the accuracy of simulation processes. Additionally, to improve ANN model performance, the selection of suitable type of transfer function with effective input combinations was thoroughly investigated before introducing the WT approach. The hybrid model (W-ANN) was also compared to the classical ANN in the prediction of 1 h ahead Ozone concentrations to insure the significance of this study. Based on statistical measures during all phases (i.e. training, validation, and testing), the W-ANN outperformed ANN model. The W-ANN model yielded fewer values of root mean square error (0.9313 ppm) and mean absolute error (0.6531 ppm) while, ANN model produced higher values of root mean square error (2.902 ppm) and mean absolute error (1.991 ppm) during the testing set. The quantity of predicted values that have absolute relative error between 1 and 3% represented 18% and 36.16% of all data points for each approach, ANN and W-ANN respectively. Additionally, the hybrid W-ANN managed successfully to forecast multiple time scales (2-, 3-, 4 and 5- ahead hour Ozone concentrations) and reported very fewer errors in comparison with modeling of one hour ahead Ozone gas concentration.

Risk assessment of extreme air pollution based on partial duration series: IDF approach

The occurrences of extreme pollution events have serious effects on human health, environmental ecosystems, and the national economy. To gain a better understanding of this issue, risk assessments on the behavior of these events must be effectively designed to anticipate the likelihood of their occurrence. In this study, we propose using the intensity–duration–frequency (IDF) technique to describe the relationship of pollution intensity (i) to its duration (d) and return period (T). As a case study, we used data from the city of Klang, Malaysia. The construction of IDF curves involves a process of determining a partial duration series of an extreme pollution event. Based on PDS data, a generalized Pareto distribution (GPD) is used to represent its probabilistic behaviors. The estimated return period and IDF curves for pollution intensities corresponding to various return periods are determined based on the fitted GPD model. The results reveal that pollution intensities in Klang tend to increase with increases in the length of time between return periods. Although the IDF curves show different magnitudes for different return periods, all the curves show similar increasing trends. In fact, longer return periods are associated with higher estimates of pollution intensity. Based on the study results, we can conclude that the IDF approach provides a good basis for decision-makers to evaluate the expected risk of future extreme pollution events.

Space Observations and Global Climatic Data Reanalysis in AERMOD Modeling Package to Enhance the Industrial Air Pollution and Health Risk Assessment

We try to enhance the AERMOD industrial pollution dispersion model with remote sensing observations and climatic models based on them. In this paper, we focus on surface parameters (albedo, roughness, Bowen ratio) and land use classification on which they depend. We model maximum hourly concentrations and the resulting acute health risk and assess the effect on them produced by using remote sensing data for local areas around industrial plants instead of global standard AERMOD parameters. We consider five real multi-source plants for the effect of classification and two of them for the effect of surface parameters. The effect on the critical pollutant is measured in three ways: a) as difference between the yearly maxima of hourly concentrations of a critical pollutant (“absolute”); b) the same limited to daytime workhours and 95% quantile instead of absolute maximum (“regulatory”); c) as maximum hourly difference over a year (“instant”). The measure of effect is divided either by the reference concentration of the pollutant, which yields the impact on health risk, or by the concentration obtained with AERMOD standards, which yields relative measure of impact. For a), the impact of roughness dominates, that of albedo is small and that of the Bowen ratio is almost zero. For b), the impact of roughness is less prominent, and that of albedo and Bowen ratio is noticeable. For c), the impact is considerable for all three parameters. The effect of land use classification is considerable in all three cases a) - c). We provide the figures for different measures of remote sensing data effect and discuss the perspective of using remote sensing data in regulatory context.

Indoor versus Outdoor Air Quality during Wildfires.

The human behavioral modification recommendations during wildfire events are based on particulate matter and may be confounded by the potential risks of gas-phase pollutants such as polycyclic aromatic hydrocarbons (PAHs). Moreover, the majority of adults spend over 90 percent of their time indoors where there is an increased concern of indoor air quality during wildfire events. We address these timely concerns by evaluating paired indoor and outdoor PAH concentrations in residential locations and their relationship with satellite model-based categorization of wildfire smoke intensity. Low-density polyethylene passive air samplers were deployed at six urban sites for 1 week in Eugene, Oregon with matched indoor and outdoor samples and 24 h time resolution. Samples were then quantitatively analyzed for 63 PAH concentrations using gas-chromatography-tandem mass spectrometry. A probabilistic principal components analysis was used to reduce all 63 PAHs into an aggregate measure. Linear regression of the first principal component against indoor versus outdoor shows that indoor gas-phase PAH concentrations are consistently equal to or greater than outdoor concentrations. Regression against a satellite-based model for wildfire smoke shows that outdoor, but not indoor gas-phase PAH concentrations are likely associated with wildfire events. These results point toward the need to include gas-phase pollutants such as PAHs in air pollution risk assessment.

Health risk and exposure assessment of indoor air pollutants in Shenzhen, China

Health risk and exposure assessment of indoor air pollutants in Shenzhen, China

A pragmatic public health-driven approach to enhance local air quality management risk assessment in Wales, UK

Air pollution, poor health and deprivation are inextricably linked. These stressors can combine to create a triple jeopardy effect where more deprived individuals and communities can be disproportionately affected by exposure to air pollution. Despite acknowledgement of this, however, the current statutory Local Air Quality Management regime prescribes that air pollution risks are considered in isolation. This project aimed to develop and test application of a practical method for carrying out air pollution risk assessment in the context of wider health determinants.A number of data components describing health, air pollution and deprivation at small area level were identified for one health board area (comprising two local authority areas) in Wales for 2011-15. These data were then combined within each of the triple jeopardy domains and then overall to assign each small area a prioritisation score to inform air quality management action. Areas were then ranked in order with a view to identifying priority areas (and clusters) for integrated air quality management and public health intervention. Local environmental and public health stakeholders were involved throughout the process and asked to provide feedback on the approach, particularly in relation to applying it in practice and evaluating its merit in terms of helping achieve local and national wellbeing policy goals.The piloted tool - called Health and Air Pollution Risk Assessment/Area Prioritisation (HAP-RAP) - offered a contemporary public health-driven approach to risk assessment intended to complement existing [narrow focus] prescribed air quality management approaches. It highlighted areas for action that were different in location, scale and size from local air quality management areas declared through existing processes. Further, stakeholder comments suggested the approach can help support more collaborative, effective and efficient ways of working, facilitate stronger policy and practice integration and achieve greater population health impact.

A novel computational solution to the health risk assessment of air pollution via joint toxicity prediction: A case study on selected PAH binary mixtures in particulate matters

Regional haze episode has already caused overwhelming public concern. Unraveling the health effects of the representative composition mixtures of atmospheric fine particulate matters (PM2.5) becomes a top priority. In this study, a novel computational solution integrating chemical-induced genomic residual effect prediction with in vitro-based risk assessment is proposed to obtain the cumulative health risk of typical chemical mixtures of particulate matters (PM). The joint toxicity of binary mixtures is estimated by analyzing both genomic similarity and dose-response curve of relevant pollutants for the chemical-induced genomic residual effect. Specifically, the modified relative potency factor (mRPF) of mixtures is introduced for this purpose, and the ratio of activation (RA) value is defined to assess the corresponding health risks of the mixtures. As a methodology demonstration, the health risk of typical binary polycyclic aromatic hydrocarbon (PAH) mixtures in PM, containing Benzo[a]pyrene (BaP) as a component, is assessed using the proposed solution. Our results indicate that the combined effect of pairwise PAHs of BaP with Benzo[b]fluoranthene (BbF) and Benz[a]anthracene (BaA) is synergistic on p53 pathway, and that the health risk of the such mixtures increases compared to that of the individual ones. Obviously, the cumulative health risk of environmental mixtures will be underestimated when the synergistic effect is wrongly assumed to be additive. To our knowledge, this is the first study ever report on a computational solution to the health risk assessment of environmental pollution via joint toxicity prediction. The novel methodology proposed here makes full use of the open-access in vitro assay data and transcriptomic information in literatures and provides a successful demonstration of the concept of systems biology and translational science.

Wintertime air pollution and health risk assessment of inhalation exposure to polycyclic aromatic hydrocarbons in rural China

Household air pollution is one important environmental risk to human health in China, however, rural air pollution is often underappreciated and field measurements are limited compared to studies in urban area. The present study investigated indoor and outdoor polycyclic aromatic hydrocarbons (PAHs), and population inhalation exposure from two rural counties in Shanxi and Guizhou provinces, respectively. The indoor levels were higher than the corresponding outdoor concentration in both sites, which was mainly affected by the indoor fuel combustion emissions. A majority of particulate PAHs was found in submicron PM1.0. Fuel types had significant impacts on the total PAHs mass concentration but also composition profiles. In homes using electricity, the PAHs concentration was lower than those burning solid fuels, and there were relatively more fractions of low molecular weight PAHs with 2–3 rings, while for those burning solid fuels, higher fractions of high molecular weight PAHs with 5–6 rings may pose larger adverse health impacts. Although the daily inhalation exposure level for the population using electricity was much lower than those using solid fuels, the estimated Incremental Lifetime Cancer Risk still exceeded the deemed safe risk of 10−6. Inhalation exposure amounts measured by using portable carried samplers were compared to the estimation based on area concentration. The substantial discrepancy between them confirmed a preferable use of portable carried samplers in exposure evaluation and health risk assessment.

Study on Air Pollution and Control Investment from the Perspective of the Environmental Theory Model: A Case Study in China, 2005–2014

China has been suffering from serious air pollution for years due to rapid industrialization. However, the relationship between China’s air pollution and pollution control schemes remains understudied in the Chinese air pollution literature. Using the Environmental Theory Model, this paper studies the relationship between air pollution and control investment in China for the period 2005–2014 and applies the inverse distance weighted interpolation (IDW) and Pearson correlation methods. As a result, this paper puts forward some policy suggestions for the governance of air pollution in China. The results are as follows: (1) The Pearson correlation coefficient between China’s air pollution index (API) and control investment is 0.466 (p &lt; 0.01). This shows that the phenomenon of ‘Treatment after Pollution’ still exists in China’s economy; (2) there is an inverted U-shaped relationship that is in accordance with the environmental Kuznets curve between China’s air pollution control investment and air pollution; (3) the high-effectiveness of governmental air pollution control is reflected in the 2013–2014 period, where the API of year 2014 decreased by 10.45 from 2013. This shows a one-year lag between exposure to air pollution and the start of control investment. Future research is warranted to concentrate on establishing a model of the relationship between air pollution and control investment or an air pollution risk assessment based on the proportional hazards model (COX) model.

Human health risk assessment of major air pollutants at transport corridors of Delhi, India

The present study undertake an assessment of human health risk regarding mortality and morbidity induced by multiple air pollutants prevailing at 36 transport corridors of the National Capital Territory (NCT) of Delhi, India. The study, covering PM10, PM2.5, SO2 and NO2, utilized the Risk of Mortality/Morbidity due to Air Pollution (Ri-MAP) model in a bid to assess the direct health impacts in the year 2016. The World Health Organization (WHO) guidelines were used to calculate mortality and morbidity for the population in 4 km2 grid sizes in the vicinity of all transport corridors and the results indicate that aggravated by the vehicular traffic, the highest number of excess cases of relative excess mortality respiratory, cardiovascular and total mortality were reported at ISBT Flyover (365, 1399 and 2136), closely followed by Wazirabad Road (362, 1378 and 2096) respectively. These two transport corridors also recorded a maximum number of excess cases of morbidity regarding hospital admission due to COPD (Chronic Obstructive Pulmonary Disease) and cardiovascular illness as 18,979 and 4762 as well as 18,969 and 4761 respectively. Further, excess numbers of cases were reported in 4 km2 grid sizes alongside the transport corridors throughout the megacity of Delhi, thereby presenting a very plausible scenario of traffic-induced human health risk in different residential and other areas. Such studies with a more focussed approach would help not only towards a better transport corridor planning but also help health institutions to be preferable to control excess number of such peculiar health cases in the city and elsewhere.