Air Pollution Impact Assessment Research Articles

Air Pollution Impact Assessment of Gresik Industrial Area (KIG) Based on Neighborhood Community in Gresik District

Air Pollution Impact Assessment of Gresik Industrial Area (KIG) Based on Neighborhood Community in Gresik District

Evaluating air quality by combining stationary, smart mobile pollution monitoring and data-driven modelling

Air pollution impact assessment is a major objective for various community councils in large cities, which have lately redirected their attention towards using more low-cost sensing units supported by citizen involvement. However, there is a lack of research studies investigating real-time mobile air-quality measurement through smart sensing units and even more of any data-driven modelling techniques that could be deployed to predict air quality accurately from the generated data-sets. This paper addresses these challenges by: a) proposing a comparative and detailed investigation of various air quality monitoring devices (both fixed and mobile), tested through field measurements and citizen sensing in an eco-neighbourhood from Lorraine, France, and by b) proposing a machine learning approach to evaluate the accuracy and potential of such mobile generated data for air quality prediction. The air quality evaluation consists of three experimenting protocols: a) first, we installed fixed passive tubes for monitoring the nitrogen dioxide concentrations placed in strategic locations highly affected by traffic circulation in an eco-neighbourhood, b) second, we monitored the nitrogen dioxide registered by citizens using smart and mobile pollution units carried at breathing level; results revealed that mobile-captured concentrations were 3–5 times higher than the ones registered by passive-static monitoring tubes and c) third, we compared different mobile pollution stations working simultaneously, which revealed noticeable differences in terms of result variability and sensitivity. Finally, we applied a machine learning modelling by using decision trees and neural networks on the mobile-generated data and show that humidity and noise are the most important factors influencing the prediction of nitrogen dioxide concentrations of mobile stations.

Evaluation and uncertainty estimation of the impact of air quality modelling on crop yields and premature deaths using a multi-model ensemble

This study promotes the critical use of air pollution modelling results for health and agriculture impacts, with the primary goal of providing more reliable estimates to decision makers. To date, the accuracy of air quality (AQ) models and the effects of model-to-model result variability (which we will refer to as model uncertainty) on impact assessment studies have been often ignored, thus undermining the robustness of the information used in the decision making process and the confidence in the results obtained.A suite of twelve PM2.5 and ozone concentration fields produced by regional-scale chemistry transport Air Quality (AQ) models during the third phase of the Air Quality Model Evaluation International Initiative (AQMEII) has been used to calculate the impact of air pollution on premature deaths and crop yields. An innovative technique is applied to bias-adjust the models to available observations.The model results for ozone and PM2.5 are combined in a multi-model (MM) ensemble, which is used to estimate the damage and economic cost to human health and crop yields, as well as the associated uncertainties. The MM ensemble quantifies directly the uncertainty introduced by AQ models into the air pollution impact assessment chain, while the indirect use of experimental information through a bias adjustment, reduces the uncertainty in the ozone and PM2.5 fields and subsequently the uncertainty of the final impact assessment and cost valuation.The analysis over the European countries analysed in this study shows a mean number of premature deaths due to exposure to PM2.5 and ozone of approximately 370,000 (inter-quantile range between 260,000 and 415,000) and a relative yield loss of approximately 7% to 9% (depending on the exposure metrics used, for wheat and maize together). Furthermore, the results indicate that a reduction in the uncertainty of the modelled ozone by 61% and by 80% (depending on the aggregation metric used) and by 46% for PM2.5, produces a reduction in the uncertainty in premature mortality and crop loss of >60%, and of an equivalent percentage in the final uncertainty of cost valuation, providing decision makers with more accurate estimations for more targeted interventions.

Update of the Exposure Response Function for the Evaluation of the Impact of PM2.5 on Natural Mortality

Background/Aim: Epidemiologic evidence provides a reliable basis for air pollution impact assessment summarized in the form of exposure-response functions (ERFs) that quantify the increase in the risks of mortality in relations to exposure to different levels of air pollution. A WHO Regional Office for Europe document (HRAPIE, 2013) provided rationale and indications in order to perform health impact assessment of air pollution (in the context of cost-benefit analysis of policies at European level) based on linear or log-linear functions relating particulate matter of a diameter less than 2.5 µm (PM2.5) to natural mortality and other specific outcomes. In the HRAPIE report, the meta-analysis by Hoek (2013) was based on 11 studies and provided the ERF for the PM2.5-all-cause (or natural-cause) mortality association (6% excess mortality, 95% Confidence Interval, CI = 4-8.3%, per 10 µg/m3 PM2.5). Methods: We reviewed 19 studies available until December 2016 on the relationship between long-term exposure to PM2.5 and natural mortality (10 studies included in Hoek et al, the extension of the Canada National Cohort, and 8 new studies). We performed meta-analysis using random effects methods of DerSimonian and Laird (1986). Results: The new synthesis indicates a summary effect estimate considerably higher (10%, 95% CI = 6-14% per 10 µg/m3 PM2.5 over the range of 5-30 µg/m3) than the value previously estimated. The resulting ERF tends to be non-linear with higher coefficients in the region 5-20 µg/m3 and lower values above 20 µg/m3. There are few observations above an annual average of 20 µg/m3, as there are few epidemiological studies on mortality risk from long-term exposure to PM2.5 in the world’s most polluted regions. Conclusions: Given the importance of health impact estimation for normative and policy evaluation activities, including Sustainable Development Goals reporting, the development of stable exposure-response functions is key and natural mortality represents a reliable epidemiologic measure. Scientific literature is progressing and adaptation and improvement of the exposure-response functions over time is also needed.

Air pollution impact assessment in the area surrounding the industrial settlement of Priolo/Augusta (Italy): A multidisciplinary approach.

Background. During the past years air pollution impact on environment and health in areas surrounding industrial sites has received an increasing attention in order to prevent or minimize adverse effects or clean-up compromised ecosystems. The measurement of pollutants emissions into the environment by chemical analysis provide little information on the toxicological activity of the contaminants. Biological monitoring assesses the effects of air mixtures on reactive organisms, highlighting the interactions among individual compounds. Exposure to air pollutants causes adverse effects both on environment, agriculture and human health. Aim. In order to evaluate the impact of atmospheric pollutants emitted by the industrial settlement of Priolo/Augusta (Italy) heavy metals (Pb, Cd, As, V, Hg, Rh, Pd, Pt, Ni) levels in air were monitored in the year 2010 and Vibrio fischeri test was used to appraise airborne pollutant ecotoxicity. Method. Sampling and determination of heavy metals was performed according to UNI EN 14902. From filtres it was made an aqueous suspensions and measured the ecotoxicity (EC50 values) of samples. Statistical analysis is made by R software. The inhibition levels and effective toxicity concentrations of these samples and solutions were determined. Interactive toxicity effects among the metals were investigated. Results. Pb, Cd, As and Ni were found in trace amounts but always below law limits 155/2010. Hg, Rh, Pd and Pt were always below the detection limit. The impacts of the single heavy metal solutions were compared with each other, a toxicity ranking of Cd>Pb>As>V>Ni was obtained in order of decreasing severity. The total effective concentrations of these five metals were in the ranges of 0.094–0.543 µg/mc. The interactive toxicity effects of the heavy metals in samples were classified as antagonistic. Conclusion. High levels of heavy metals may constitute an important input in the biochemical cycle and may have significant impacts, but our findings are not considered concern for human health.

An assessment of air pollution impact for an Indian highway project

PurposeThe paper aims to demonstrate a geographic information system (GIS) based study on environmental impact assessment (EIA), due to air pollution, for a highway project.Design/methodology/approachAn approach has been designed to explore the scope for the combination of EIA and GIS in development for the proposed Allahabad Bypass Project. The air quality in the study area has been quantified in terms of the air pollution index (API). GIS has been exploited to obtain the spatial information for the prediction of air pollution impact at different suburban and rural areas adjacent to the stretch of bypass.FindingsThe study has enabled the researchers to understand the variation in air quality along the total stretch of the bypass keeping in view the “with” and “without” project scenarios. The results obtained from the study show considerable increase in air pollution levels from baseline to the projected period of 20 years, due to gradual increase in vehicular traffic along the highway.Originality/valueThe information presented in this paper serves as an example to quantify the negative impacts of countryside air quality associated with highway projects. The approach utilized the spatial evaluation of air pollution and helps to provide a critical insight to the problem, which is not apparent while carrying out such an exercise in the traditional manner.Practical implicationsHopefully, this study will encourage the highway planners in India to make a wider application of the technique for an indepth assessment of environmental impacts.

Air pollution impact assessment on agroecosystem and human health characterisation in the area surrounding the industrial settlement of Milazzo (Italy): a multidisciplinary approach

In order to evaluate the impact of atmospheric pollutants emitted by the industrial settlement of Milazzo (Italy) on agriculture, sulphur dioxide and ozone levels in air were monitored and the data were used to estimate yield losses of the most widespread cultures. Trace element concentrations in crops and soils were also detected and metabolic profiles of soil microbial communities were considered. Vibrio fischeri test was used to appraise airborne pollutant ecotoxicity and epidemiological studies on causes of death distribution were carried out to characterize health state of people living in the area. All the sampling points were selected in farms on the basis of a theoretical meteo-diffusive model of industrial air pollutants. Experimental SO2 and O3 values mainly exceeded the threshold established by Italian and EU regulations to protect vegetation and they correspond to estimated significant crop losses. Conversely toxic element residues in soils and in agroalimentary products were generally lower than the fixed values. SO2 and O3 concentrations, toxic element contents and ecotoxicity levels of airborne pollutants were not related only to industrial site emissions, while the fluctuations on metabolic profiles of soil microbial communities seem to agree with the predicted deposition of xenobiotic compounds from the industrial plants. The epidemiological study evidenced a better health state of populations living in the investigated area than in the Messina province and the Sicily region but, inside the area, males living in the municipalities closest to the industrial settlement exhibited a worst health state than those in the very far ones.

Assessment of the status of biogenic organic emissions and impacts on air quality in southern Africa

Air quality management in South Africa has traditionally focused on industrial, vehicular and domestic coal burning as emission sources of air pollution. Only recently through, research initiatives such as Southern African Fire-Atmosphere Research Initiative in 2000 (SAFARI 2000) and the Cross Border Air Pollution Impact Assessment Project, have the importance of biogenic volatile organic compound (BVOC) emissions been recognized in regional atmospheric chemistry and composition, particularly relating to surface ozone formation. These projects have identified significant gaps in the understanding of BVOC emissions in southern Africa.BVOC emissions are relatively well understood for southern African savanna and woodland plant species and landscapes. Considering that the region is home to more than 20 000 plant species, the most significant gap in the understanding of BVOC emissions is the acute lack of plant specific emission information. Equally important is an understanding of the unique local factors that control BVOC emissions.A project has been launched in South Africa to develop capacity and technologies to address the BVOC knowledge gaps. It focuses on measurement and modelling and aims to develop a cadre of skilled scientists in BVOC sampling techniques using leaf and branch enclosures, relaxed eddy accumulation and lidar techniques in conjunction with development and application of photochemical modelling.

Modelled surface ozone over southern Africa during the Cross Border Air Pollution Impact Assessment Project

Monitoring of surface ozone over southern Africa has shown that ambient concentrations often exceed a threshold of 40 ppb at which damage to vegetation by ozone could be expected. The Cross Border Air Pollution Assessment Project (CAPIA) was therefore established to assess the potential impacts of ozone on maize, a staple food crop, in five southern African countries. Measured surface ozone data are scare in the region so it was necessary to complement the monitoring with regional-scale photochemical modelling to achieve the objective. The Pennsylvania State and NCAR Mesoscale Model (MM5) is used to produce gridded meteorological data for 5 days in each month of the maize growing season, October to April, as input to the photochemical model, CAMx. Gridded anthropogenic emissions from industry, transport and domestic burning and gridded biogenic emissions from soils and vegetation are input to CAMx. The model estimations indicate large areas on the sub-continent where surface ozone concentrations exceed 40 ppb for up to 10 h per day. Maximum concentrations may exceed 80 ppb, particularly in the winter when mean ozone concentrations are higher. The areas where the 40 ppb threshold is exceeded coincide with maize growing areas in South Africa and Zimbabwe. It appears that neither anthropogenic emissions nor biogenic emissions are dominant in the production of surface ozone over southern Africa. Rather the formation of surface ozone over the region is attributed to the combined contribution of precursors from anthropogenic and biogenic origin.

Surface ozone over southern Africa: synthesis of monitoring results during the Cross border Air Pollution Impact Assessment project

Abstract Measurements of surface ozone in the southern African region are limited to a few active and passive monitoring sites. Over the region, the mean surface ozone concentrations exhibit strong seasonal and diurnal variations. The seasonal maximum generally occurs in the spring months from August to November and the minimum occurs in December and January. With the exception of Cape Point, a strong diurnal variation is observed at all sites. Ozone concentrations increase from a minimum near sunrise to a maximum in the afternoon, then decrease again to the early morning minimum. The highest ozone concentrations occur over Botswana and the Mpumalanga highveld. In both regions the springtime maximum is between 40 and 60 ppb, but reached more than 90 ppb as a mean in October 2000. In these two regions the monthly minimum is between 20 and 30 ppb. The mean daytime ozone concentrations in Botswana and on the highveld reach 40 ppb as early as 10:00 and remain above this level for up to 10 h. At the background stations at Cape Point, in Namibia and areas adjacent to the highveld the maximum concentrations are between 20 and 30 ppb with minimums between 10 and 20 ppb. In the Cross border Air Pollution Impact Assessment project, CAPIA, a threshold value of 40 ppb is used to assess the potential risk of damage to maize by ozone. Measured data show that this threshold is exceeded over Botswana and on the South African highveld.

Assessment of air pollution from small scale industry.

Air pollution due to small scale industries have been found to cause serious occupational health hazards and adverse effects on vegetation and heritage. The study for air pollution impact assessment for brick kiln industries was undertaken. The stack monitoring exercise was carried out to estimate the pollution level of SPM, SO2, and NOx. The ambient air quality was also measured in the vicinity of brick kilns to assess the impact of stack emission on ground level concentration. Characterisation of SPM for toxic metals were studied. Modelling exercise was carried to predict the impact of emission of brick kiln on surrounding environment. To minimise the emission level and ground level concentration, air pollution mitigation measures are suggested.

Assessment of air pollution impact

Several essential steps of air quality assessment are described, including identification, prediction, and evaluation of critical variables and potential changes of air quality. A coal-reconversion power plant in New York was selected as an example to illustrate the assessment.