Aspects Of Air Quality Research Articles

The Impact of Air Pollution from Industrial Fires in Urban Settings: Monitoring, Modelling, Health, and Environmental Justice Perspectives

Industrial fires at facilities including waste management sites, warehouses, factories, chemical works, and fuel storage depots are relatively frequent occurrences. Often, these fires occur adjacent to urban communities and result in ground-level airborne pollutant concentrations that are well above guideline values. Land, water, livestock, and crops may also be contaminated by the emissions and by firefighting activities. Moreover, impacted communities tend to have a higher proportion of minority ethnic populations as well as individuals with underlying health vulnerabilities and those of lower socio-economic status. Nevertheless, this is an aspect of air quality that is under-researched, and so this review aims to highlight the public health hazards associated with industrial fires and the need for an effective, coordinated, public health response. We also review the range of monitoring techniques that have been utilised in such fires and highlight the role of dispersion modelling in predicting plume trajectories and in estimating population exposure. We recommend establishing 1 h guideline values for particulate matter to facilitate timely public health interventions, and we highlight the need to review regulatory and technical controls for sites prone to fires, particularly in the waste sector.

Effects of indoor plants on CO2 concentration, indoor air temperature and relative humidity in office buildings.

This experimental study investigates the influence of indoor plants on three aspects of air quality in office spaces: relative humidity, indoor air temperature, and carbon dioxide concentration. Employing a Latin square design, we rotated three different treatments across three offices over six time periods. These treatments included a control (no plants), a low-volume treatment (five plants), and a high-volume treatment (eighteen plants) of Nephrolepis exaltata (Boston fern). Air quality parameters were continuously monitored at five-minute intervals using Trace Gas Analyzers. Generalised linear mixed modelling (GLMM) was employed to examine the effect of each treatment on relative humidity, indoor air temperature and CO2 concentration. We observed a significant positive correlation between the number of indoor plants and relative humidity levels. In offices without any plants, the median relative humidity was 29.1%. This increased to 38.9% in offices with 5 plants and further to 49.2% in offices with 18 plants. However, we did not find significant associations between the number of indoor plants and indoor air temperature or corrected CO2 concentration. Our research provides support for the use of indoor plants to increase relative humidity, which can have health benefits in dry climates, but does not provide support for using indoor plants to regulate indoor air temperatures or CO2 concentration in office environments.

Prediction of PM2.5 with a piecewise affine model considering spatial-temporal correlation

Over the past several decades, several air pollution prevention measures have been developed in response to the growing concern over air pollution. Using models to anticipate air pollution accurately aids in the timely prevention and management of air pollution. However, the spatial-temporal air quality aspects were not properly taken into account during the prior model construction. In this study, the distance correlation coefficient (DC) between measurements made in various monitoring stations is used to identify appropriate correlated monitoring stations. To derive spatial-temporal correlations for modeling, the causality relationship between measurements made in various monitoring stations is analyzed using Transfer Entropy (TE). This work explores the process of identifying a piecewise affine (PWA) model using a larger dataset and suggests a unique hierarchical clustering-based identification technique with model structure selection. This work improves the BIRCH (Balanced Iterative Reducing and Clustering using Hierarchies) by introducing Kullback-Leibler (KL) Divergence as the dissimilarity between clusters for handling clusters with arbitrary shapes. The number of clusters is automatically determined using a cluster validity metric. The task is formulated as a sparse optimization problem, and the model structure is selected using parameter estimations. Beijing air quality data is used to demonstrate the method, and the results show that the proposed strategy may produce acceptable forecast performance.

A novel multicriteria methodology to assess the renovation of social buildings

The current Energy Performance Certificates of buildings are mostly based on the expected energy consumption. Recently, some certification schemes are starting to incorporate Indoor Air Quality aspects, but it is still not usual. Another topic of interest, such as energy poverty, is not considered in current certification schemes either. This paper presents a novel multicriteria methodology to assess the renovation of social housing buildings: the ARCAS methodology. The novelty lies in its transversal approach, which considers three axes: Energy Efficiency, Energy Poverty, and Indoor Environment Quality. The indicators set for assessment are calculated based on actual on-site measurements. The methodology has been tested in six demonstrator buildings selected throughout the SUDOE territory (southwestern Europe). The results show that the ARCAS methodology allows a comprehensive assessment of the current situation of the building to be achieved and helps to propose the renovation measures in a specific direction. Advice and guidance for professionals who want to test the methodology are also given. Although the methodology has been developed for its application in social housing, according to the EU recommendations, it can be applied to any type of housing.

A grid independence study to select computational parameters in dust storm prediction models: A sensitive analysis

Grid options are computational parameters that lead to proper numerical accuracy in air quality simulation and their selection is challenging. Therefore, the present study intends to provide a framework for selecting grid options. In this paper, the impact of five computational parameters such as time step, modeling duration, computational domain, and vertical and horizontal resolution on predicting a severe dust storm was investigated by WRF-Chem. A two-step algorithm based on the grid independence framework was proposed to select the appropriate grid options. In total, >22 different configurations were considered to investigate the effect of these options. Also, grid options were prioritized by wins in the league (WIL) theory to evaluate factors affecting numerical results. The results showed that the choice of computational parameters has a significant effect on prediction. Inappropriate computational domain and modeling duration cannot accurately predict the intensity of the dust storm and these two parameters have the highest effect on the numerical modeling. The results of WIL approach showed the proposed algorithm was able to appropriately estimate the dust storm. The proposed framework can be used not only in predicting dust storms but also in predicting weather conditions and other aspects of air quality.

Toward a critical assessment of indoor environmental quality standards

Building design and operation requirements regarding indoor-environmental quality (IEQ) are of direct relevance to occupants' needs. In most buildings, occupant-related requirements pertain to the provision of conditions that support optimal task performance and are subjectively perceived as comfortable or pleasant. Codes, standards, and guidelines that specify IEQ requirements are commonly viewed as the main sources of reference for practitioners, who are expected to follow the provisions in these documents and provide corresponding proof of compliance. However, actual code compliance processes are not always accompanied by critical reflections regarding the evidentiary basis of the entailed mandates and recommendations. It is thus necessary to critically scrutinise standards in view of explicit or implicit references to the scientific basis of the entailed mandates. The present contribution explores and details a path toward such a critical assessment. To this end, we considered a number of typical and frequently referenced standards pertaining to thermal, visual, and air quality aspects of indoor environments. The results of this illustrative assessment effort highlight the scope and limitations of the standards' default approaches to the definition of IEQ-relevant requirements. Moreover, they point to considerable gaps in the chain of evidence from standards' immediate content to the underlying factual sources.

Оценка и картографирование качества атмосферного воздуха регионов России с использованием материалов дистанционного зондирования Земли

The authors present a method of joint and separate use of remote sensing data and state statistics to assess the quality of atmospheric air in Russian regions. The simultaneous use of information obtained from various sources and characterizing different aspects of air quality enables assessing the subject of the study better. The emission data was obtained from the State Report “About conditions and protection of the environment in the Russian Federation in 2019”, and that from the AURA/OMI was used to assess the pollutants concentrations. The methodology is based on the aggregation of various pollutants’ emission indicators and their concentration in the atmospheric column into integral indices using Cartesian distances to the worst unit. It is shown that each index separately does not make an objective picture of the air quality. A typological approach was applied to identify the regions similar in terms of the structure of anthropogenic impact on the atmospheric air, as well as to the content of major pollutants. Five typological groups for emissions and six ones for the content of pollutants were identified. The integral air quality index was calculated and the corresponding maps were compiled using heterogeneous data. It is shown that such an approach differentiates the regions much more clearly and makes it possible to draw more accurate conclusions on the quality of the atmospheric air.

Regional evaluation of the performance of the global CAMS chemical modeling system over the United States (IFS cycle 47r1)

Abstract. The Copernicus Atmosphere Monitoring Service (CAMS) provides routine analyses and forecasts of trace gases and aerosols on a global scale. The core is the European Centre for Medium Range Weather Forecasts (ECMWF) Integrated Forecast System (IFS), where modules for atmospheric chemistry and aerosols have been introduced and which allows for data assimilation of satellite retrievals of composition. We have updated both the homogeneous and heterogeneous NOx chemistry applied in the three independent tropospheric–stratospheric chemistry modules maintained within CAMS, referred to as IFS(CB05BASCOE), IFS(MOCAGE) and IFS(MOZART). Here we focus on the evaluation of main trace gas products from these modules that are of interest as markers of air quality, namely lower-tropospheric O3, NO2 and CO, with a regional focus over the contiguous United States. Evaluation against lower-tropospheric composition reveals overall good performance, with chemically induced biases within 10 ppb across species for regions within the US with respect to a range of observations. The versions show overall equal or better performance than the CAMS reanalysis, which includes data assimilation. Evaluation of surface air quality aspects shows that annual cycles are captured well, albeit with variable seasonal biases. During wintertime conditions there is a large model spread between chemistry schemes in lower-tropospheric O3 (∼ 10 %–35 %) and, in turn, oxidative capacity related to NOx lifetime differences. Analysis of differences in the HNO3 and PAN formation, which act as reservoirs for reactive nitrogen, revealed a general underestimate in PAN formation over polluted regions, likely due to too low organic precursors. Particularly during wintertime, the fraction of NO2 sequestered into PAN has a variability of 100 % across chemistry modules, indicating the need for further constraints. Notably, a considerable uncertainty in HNO3 formation associated with wintertime N2O5 conversion on wet particle surfaces remains. In summary, this study has indicated that the chemically induced differences in the quality of CAMS forecast products over the United States depends on season, trace gas, altitude and region. While analysis of the three chemistry modules in CAMS provide a strong handle on uncertainties associated with chemistry modeling, the further improvement of operational products additionally requires coordinated development involving emissions handling, chemistry and aerosol modeling, complemented with data-assimilation efforts.

The impact of COVID-19 pandemic on nitrogen dioxide levels in Nigeria.

The Coronavirus disease (COVID-19) has been transmitted worldwide over a very short time after it originated in China in December 2019. In an attempt to control its spread and reduce its health impacts, several countries including those in the African continent imposed restrictive measures that was termed “lockdown”. The outcomes of this lockdown have been reported to be beneficial to air quality worldwide. The main objective of this study is to assess the impact of lockdown due to COVID-19 on nitrogen dioxide (NO2) levels over six major cities in Nigeria. Maps extracted from satellite (Sentinel-5P) were used to indicate the significant reduction in the level of NO2 in the selected cities in Nigeria during two time-intervals, pre-lockdown (December, 2019) and during lockdown (April, 2020). The results show a significant reduction in NO2 levels during the lockdown period compared with its levels during the pre-lockdown period in 2019. The reduction in NO2 concentration levels during lockdown is likely due to less traffic, social distancing and restrictions on business and human activities. There could be an element of uncertainty in the results due to seasonality, as the comparison is done with a different season. However, the magnitude of change due to lockdown is probably much higher than the seasonal variability. Although COVID-19 has negatively impacted the health and economic status of all regions worldwide, it has benefited some aspects of air quality in most countries including Nigeria. This indicates that anthropogenic activities may be managed to reduce air pollution and positively impact the health of human beings.

Comparative assessments and insights of data openness of 50 smart cities in air quality aspects

Data Openness is considered as an indispensable component for scientific innovation, community engagement and smart city development. In this study, a Data Openness in Air Quality (DOAQ) framework that consists of 3 tiers with a total of 23 open data principles was established to assess and monitor the status and development of data sharing, release and centralization of air quality information in the top 50 smart cities (Top50SC) around the world. The DOAQ utilizes additive formulas with predefined coefficients to obtain scores in each tier, thus reflecting the relative importance on data availability and visibility of different air quality data. The scores of DOAQ were compared with the smart cities scorings from Eden Strategy Institute and ONG&ONG Pte Ltd. (2018), and other socioeconomic attributes (i.e., social, political and humane) within the current study. Strong correlations (i.e., 0.4−0.6) among these indices implicate that the status of air quality reporting could be a good proxy to gauge the environmental data openness in a city. Lastly, good practices (e.g., apps and air quality forecasts), essential criteria and directions for future smart city development on air quality reporting were summarized, with the aim of laying down practical and efficient guidelines for individual smart city that desires to seek for improvements in air quality data openness.

Impact of Ambient Particulate Matter and Ozone Exposure of Heart Transplant Recipients on All-Cause Mortality after Heart Transplant

Purpose There is limited evidence on role of air quality on chronic rejection after heart transplant (HT). We investigated the impact of particulate matter concentration (PM≥2.5 μm/m3) and ozone (O3) exposure of recipients on all-cause mortality after HT in the US. Methods UNOS Standard Transplant Analysis and Research (STAR) database (June 30, 2017) identified adult HT recipients between 2005 and 2015, and their zip code of residence at HT. Average ambient PM and daily maximum 8-hour average O3 associated with recipient residencies 1 year after HT were estimated by mapping each zip code to a census tract, using a crosswalk from HUD, downscaled from a 12 × 12-km sq grid resolution detailed chemistry - transport model application using a Bayesian space-time downscaler, and then fused with surface observations. PM concentration was classified into low ( 12 μg/m3); O3 was similarly categorized (low: 42 ppb). Inverse-probability of treatment weighted Cox regression and Kaplan-Meier curves assessed the impact of PM and O3 on 1-year and long-term incidence of all-cause mortality. Results Overall, 17,893 HT patients were included; Median follow-up was 1529 days (IQR 737-2586). 21% of HT recipients had high PM exposure and 20% had high O3 exposure. While estimates were imprecise, both high exposure levels of PM and O3, compared to low exposure, appeared to increase long-term mortality (Table). High PM exposure may also increase 1-year mortality; O3 had no impact on 1-year mortality. Conclusion PM2.5 and O3 conc are only 2 aspects of air quality and appear to increase long term risk of death after HT. Additional research on other air quality measures including isolating primary and secondary components of PM2.5 and focusing on traffic-related air pollutants is warranted for all transplant recipients.

Observed Data of Forest Fire Hotspots effects on Respiratory Disorder by Arc-GIS in Riau Province, Indonesia

The paper shows that air quality aspects rise from forest fires in Indonesia and they have associations with a wide range of adverse health outcomes, including respiratory health problems. Due to the unpredictable nature of forest fires, it is challenging for public health authorities to evaluate the potential exposures before they occur reliably. Using GIS software, zoning was made om Riau Province, Indonesia. The data shows that the highest fire hotspot was in 2015 by 12,854 and the lowest was 527 in 2017 as well as the lowest Respiratory Disorder Cases in 2017 was 371,044. The Finding proves that smoke has a significant negative effect on increasing respiratory problems Therefore, it also indicates that smoke and haze forecastings are effective tools and challenging to be developed that can be used as public health predictions and establish a suitable policy on forest fires. However, their inherent uncertainties limit their widespread adoption. Observed measurements from air quality monitoring networks and remote sensing platforms are more reliable, but they are inherently retrospective.

QUALIDADE DO AR EM AMBIENTES HOSPITALARES:

O presente estudo apresenta informações referente aos aspectos científicos, normativos e legislativos da qualidade do ar no ambiente interno de unidades hospitalares, seguida de uma investigação empírica em uma unidade hospitalar na região da floresta amazônica, estado de Rondônia. O trabalho foi realizado em duas etapas, a primeira etapa consiste em apresentar revisão bibliográfica de artigos científicos, normas e leis sobre qualidade do ar em estabelecimentos de assistência à saúde, na segunda etapa foi caracterizada a realidade de uma unidade hospitalar do interior do Estado de Rondônia sobre o tema abordado. Por meio do presente trabalho foi possivel disponibilizar informações sobre a qualidade do ar interior e potenciais riscos em ambientes hospitalares, servindo de base a pesquisadores, projetistas, adminitradores, colaboradores e até mesmo pacientes, de modo a disponibilizar conhecimento de projetos, implantação, gerenciamento e riscos relacionados a sistemas de climatização em diferentes setores hospitalares, por fim, na investigação empírica foi comprovada a completa incompatibilidade com normas e legislações específicas, apresentando uma análise realista proposta para a adequação normativa e legislativa do estabelecimento.

District heating networks: an inter-comparison of environmental indicators.

The installation of district heating (DH) systems constitutes an advantage from the energetic, climate, and air quality aspects. However, the configuration and operational features of a DH system affect significantly its environmental performance. The objective of the present study is the energetic and environmental assessment of DH networks that present differences in size and operating configurations, to define relevant environmental performance indicators. Three case studies in Italy are analyzed, following a methodology based on the impact pathway approach that was presented by the authors in previous studies. Case studies are evaluated in terms of total emission, pollutant concentration (NOx, CO, PM), and health damage external costs. Results show that lower pollutant emissions are associated with the installation of a DH system compared to autonomous residential boilers. Air quality is also improved and health externalities are reduced. The results of CO2 savings are differentiated depending on the efficiency and emission factors of the systems. An inter-comparison of different cases is then presented, based on the elaboration of specific indicators of environmental and health impacts. This section shows that, besides the size of the DH system, other factors, such as population density and geographical distribution of pollutants concentration, are important. Among the indicators considered, those based on health externalities provide more complete and comparable information on the final impact of the alternative solutions on the exposed population. Their application seems thus promising for the evaluation of alternative planning strategies for DH systems.

Impact of Ambient Particulate Matter (PM) Exposure of Lung Donors and Recipients on Bronchiolitis Obliterans Syndrome (BOS) and Mortality after Lung Transplant (LT)

A Belgian study found proximity to a motorway increased risk of BOS after LT. Using zip codes as a surrogate for habitat location we investigated the impact of PM2.5 concentration (conc) (PM≥ 2.5 μm/m3) exposure of donors and recipients on BOS and mortality after LT in the US. UNOS Standard Transplant Analysis and Research (STAR) database (June 30, 2017) identified adult LT recipients and their donors between 2005 and 2015, and their zip code of residence at LT. Average ambient PM2.5 conc (PM≥ 2.5 μm/m3) associated with donor and recipient residencies 1 year prior to LT were estimated by mapping each zip code to a census tract, using a crosswalk from HUD, downscaled from a 12 × 12-km sq grid resolution detailed chemistry - transport model application using a Bayesian space-time downscaler, and then fused with surface observations. PM2.5 conc was classified into low (<8 μg/m3), medium (8-12 μg/m3) and high (>12 μg/m3) exposure categories. Cox proportional hazards regression and Kaplan-Meier curves assessed the impact of PM2.5 on 1 year and long term incidence of BOS and all cause mortality. 17,760 LT were analyzed. Median followup was 1101 days (IQR 511-2073, range 1-4448). 25% of LT had high donor exposure and 24% had high recipient exposure. Recipient exposure to PM2.5 had no impact on 1-year survival. However, higher PM2.5 donor exposure appeared to increase risk of early death, although estimates were imprecise (Table). Higher concentration of recipient or donor PM2.5 did not increase long-term mortality risk, and curiously higher recipient PM reduced BOS incidence (Table). PM2.5 is only one aspect of air quality and does not appear to increase long term risk of BOS or death after LT. Donor PM. exposure may have a small impact on 1 year survival after LT. Additional research on other air quality measures including isolating primary and secondary components of PM2.5 and focusing on traffic-related air pollutants is needed.

Investigation of Air Circulation For Indoor Air Quality Of Middle-Class Apartment in Jakarta, Indonesia

The most significant energy used in middle-class apartments is the air circulation unit. The use of energy from the air circulation system is related to the comfort of the user in the housing unit, so it adjusts to the applicable standard. The objection of this study is to investigate the optimization of the air circulation system in middle-class apartments in an urban area. The method is a comparative study of the government standard. The stages of the research did site observation, take air quality measurement, and interview with the questionnaire. Indoor air quality data collected are temperature, relative humidity, CO, and CO2. The data measurement compared to SNI 03-6572-2001 on Procedures for Designing Air Conditioning and Ventilation Systems in Buildings, Indonesian National Standardization. The questionnaire was to find out the comfort of residents on indoor air quality (IAQ). This study reveals that almost all air quality aspects are consistent to standard, except the temperature. The results of this study that meet the criteria related to air circulation are air movement 40%, relative humidity 65.5%, air movement 40%, CO 78%, and CO2 95%. The result of the questionnaires states that 72.4% of residents feel comfortable with the air quality in the dwelling unit. The size of the room and the adequacy of ventilation in the place influences the value of the air circulation system besides air movement.

Holistic approach to human comfort

ABSTRACT Consideration for human comfort in the urban plane has largely been focused on the wind speed that a pedestrian might experience due to the surrounding built form, prevailing winds and site exposure. As such, wind criteria developed by councils for precincts around the world are focused on the wind speed for safety and comfortable conditions for the intended uses. However, human comfort is not only the experienced wind force, but also temperature, relative humidity, solar radiation, clothing and other parameters. A comprehensive model has been developed by RWDI for the assessment of holistic human comfort, including seasonal climate variance. This can be further refined to consider noise and air quality aspects. This paper will demonstrate the application of a developed human comfort model which has been carried out for projects in different climate zones and the importance of considering all aspects, holistically, when determining true comfort for an outdoor microclimate.

Determination of Thermal Comfort in Indoor Sport Facilities Located in Moderate Environments: An Overview

In previous years, providing comfort in indoor environments has become a major question for researchers. Thus, indoor environmental quality (IEQ)—concerning the aspects of air quality, thermal comfort, visual and acoustical quality—assumed a crucial role. Considering sport facilities, the evaluation of the thermal environment is one of the main issues that should be faced, as it may interfere with athletes’ performance and health. Thus, the necessity of a review comprehending the existing knowledge regarding the evaluation of the thermal environment and its application to sport facilities becomes increasingly relevant. This paper has the purpose to consolidate the aspects related to thermal comfort and their application to sport practice, through a deep study concerning the engineering, physiological, and psychological approaches to thermal comfort, a review of the main standards on the topic and an analysis of the methodologies and the models used by researchers to determine the thermal sensation of sport facilities’ occupants. Therefore, this review provides the basis for future research on the determination of thermal comfort in indoor sport facilities located in moderate environments.

Improved Satellite Retrieval of Tropospheric NO2 Column Density via Updating of Air Mass Factor (AMF): Case Study of Southern China

Improving air quality and reducing human exposure to unhealthy levels of airborne chemicals are important global missions, particularly in China. Satellite remote sensing offers a powerful tool to examine regional trends in NO2, thus providing a direct measure of key parameters that strongly affect surface air quality. To accurately resolve spatial gradients in NO2 concentration using satellite observations and thus understand local and regional aspects of air quality, a priori input data at sufficiently high spatial and temporal resolution to account for pixel-to-pixel variability in the characteristics of the land and atmosphere are required. In this paper, we adapt the Berkeley High Resolution product (BEHR-HK) and meteorological outputs from the Weather Research and Forecasting (WRF) model to describe column NO2 in southern China. The BEHR approach is particularly useful for places with large spatial variabilities and terrain height differences such as China. There are two major objectives and goals: (1) developing new BEHR-HK v3.0C product for retrieving tropospheric NO2 vertical column density (TVCD) within part of southern China, for four months of 2015, based upon satellite datasets from Ozone Monitoring Instrument (OMI); and (2) evaluating BEHR-HK v3.0C retrieval result through validation, by comparing with MAX-DOAS tropospheric column measurements conducted in Guangzhou. Results show that all BEHR-HK retrieval algorithms (with R-value of 0.9839 for v3.0C) are of higher consistency with MAX-DOAS measurements than OMI-NASA retrieval (with R-value of 0.7644). This opens new windows into research questions that require high spatial resolution, for example retrieving NO2 vertical column and ground pollutant concentration in China and other countries.

A classification to align social-ecological land systems research with policy in Europe

Both research and policy recognize land systems as fundamental to human life and activities. However, these two perspectives approach land from different ends and it can be difficult to see how studied variables contribute to broader policy goals. In this paper, we argue that there is a need to better select variables to study land systems as social-ecological systems, and to align research more with those policy goals. Concentrating on the European continent, we pursue three interrelated objectives: we (1) build a classification of land systems variables, (2) examine where existing land systems research is positioned in this classification, and (3) compare a set of policies and science-policy frameworks with the classified research. To do so, we conduct a systematic review of 69 peer-reviewed, empirical land systems papers, as well as four overarching policies and science-policy frameworks. We find that over 60% of the reviewed papers include both environmental and social variables, and we identify 154 unique variables studied, 57% of which are environmental. The average paper examines four times as many environmental variables as social ones. We find that policies and science-policy frameworks stress social variables more and include health and air quality aspects that are lacking in the reviewed land systems research. Our classification can help to design research that includes both social and environmental variables and is aligned with broader policy goals. We highlight social variables with available spatial data to encourage a more balanced and integrative social-ecological research design, going beyond a focus on the built and natural environment. Our classification can contribute to guiding land systems researchers towards greater policy relevance. We hope that our classification contributes to a conversation within land systems research on the selection of variables, as well as its further development.