scholarly journals Air quality resolution for health impact assessment: influence of regional characteristics

2014 ◽  
Vol 14 (2) ◽  
pp. 969-978 ◽  
Author(s):  
T. M. Thompson ◽  
R. K. Saari ◽  
N. E. Selin
Keyword(s):  
Air Quality ◽  
Human Health ◽  
Rural Areas ◽  
Urban Areas ◽  
Health Benefits ◽  
Health Benefit ◽  
Health Impacts ◽  
Regional Characteristics ◽  
Human Health Impacts ◽  
The Impact

Abstract. We evaluate how regional characteristics of population and background pollution might impact the selection of optimal air quality model resolution when calculating the human health impacts of changes to air quality. Using an approach consistent with air quality policy evaluation, we use a regional chemical transport model (CAMx) and a health benefit mapping program (BenMAP) to calculate the human health impacts associated with changes in ozone and fine particulate matter resulting from an emission reduction scenario. We evaluate this same scenario at 36, 12 and 4 km resolution for nine regions in the eastern US representing varied characteristics. We find that the human health benefits associated with changes in ozone concentrations are sensitive to resolution. This finding is especially strong in urban areas where we estimate that benefits calculated using coarse resolution results are on average two times greater than benefits calculated using finer scale results. In three urban areas we analyzed, results calculated using 36 km resolution modeling fell outside the uncertainty range of results calculated using finer scale modeling. In rural areas the influence of resolution is less pronounced with only an 8% increase in the estimated health impacts when using 36 km resolution over finer scales. In contrast, health benefits associated with changes in PM2.5 concentrations were not sensitive to resolution and did not follow a pattern based on any regional characteristics evaluated. The largest difference between the health impacts estimated using 36 km modeling results and either 12 or 4 km results was at most ±10% in any region. Several regions showed increases in estimated benefits as resolution increased (opposite the impact seen with ozone modeling), while some regions showed decreases in estimated benefits as resolution increased. In both cases, the dominant contribution was from secondary PM. Additionally, we found that the health impacts calculated using several individual concentration–response functions varied by a larger amount than the impacts calculated using results modeled at different resolutions. Given that changes in PM2.5 dominate the human health impacts, and given the uncertainty associated with human health response to changes in air pollution, we conclude that, when estimating the human health benefits associated with decreases in ozone and PM2.5 together, the benefits calculated at 36 km resolution agree, within errors, with the benefits calculated using fine (12 km or finer) resolution modeling when using the current methodology for assessing policy decisions.

scholarly journals Air quality resolution for health impacts assessment: influence of regional characteristics

2013 ◽  
Vol 13 (5) ◽  
pp. 14141-14161 ◽  
Author(s):  
T. M. Thompson ◽  
R. K. Saari ◽  
N. E. Selin
Keyword(s):  
Air Quality ◽  
Human Health ◽  
Rural Areas ◽  
Urban Areas ◽  
Transport Model ◽  
Health Benefits ◽  
Health Impacts ◽  
Regional Characteristics ◽  
Human Health Impacts ◽  
The Impact

Abstract. We evaluate how regional characteristics of weather, population, and background pollution might impact the selection of optimal model resolution when calculating the human health impacts of changes to air quality. Using an approach consistent with air quality policy evaluation, we use a regional chemical transport model (CAMx) and a health benefits mapping program (BenMAP) to calculate the human health impacts associated with changes in ozone and fine particulate matter resulting from an emissions reduction scenario. We evaluate this same scenario at 36, 12 and 4 km resolution for nine regions in the Eastern US representing varied characteristics. We find that the human health benefits associated with changes in ozone concentrations are sensitive to resolution, especially in urban areas where we estimate that benefits calculated using coarse resolution results are on average two times greater than benefits calculated using finer scale results. In three urban areas we analyzed, results calculated using 36 km resolution modeling fell outside the uncertainty range of results calculated using finer scale modeling. In rural areas the influence of resolution is less pronounced with only an 8% increase in the estimated health impacts when using 36 km resolution over finer scales. In contrast, health benefits associated with changes in PM2.5 concentrations were not sensitive to resolution and did not follow a pattern based on any regional characteristics evaluated. The largest difference between the health impacts estimated using 36 km modeling results and either 12 or 4 km results was at most ±10% in any region. Several regions showed increases in estimated benefits as resolution increased (opposite the impact seen with ozone modeling) due to a higher contribution of primary PM in those regions, while some regions showed decreases in estimated benefits as resolution increased due to a higher contribution of secondary PM. Given that changes in PM2.5 dominate the human health impacts we conclude that human health benefits associated with decreases in ozone plus PM2.5, when calculated at 36 km resolution are indistinguishable from the benefits calculated using fine (12 km or finer) resolution modeling in the context of policy decisions.

scholarly journals Emission of fine particles (PM2.5) from residential biomass combustion in Croatia and how to reduce it

2020 ◽  
Vol 7 (2) ◽  
pp. 84-94
Author(s):  
Mirela Poljanac
Keyword(s):  
Air Quality ◽  
Human Health ◽  
Urban Areas ◽  
Fine Particles ◽  
Biomass Combustion ◽  
Rural And Urban Areas ◽  
Wood Burning ◽  
Rural And Urban ◽  
The Impact ◽  
Pm2.5 Emissions

Wood burning in residential appliances is very represented in the Republic of Croatia. It is a main or an additional form of heating for many households in rural and urban areas and is therefore an important source of air pollution. The choice of energy and the combustion appliance used in home have a significant impact on PM2.5 emissions. The paper informs the reader about PM2.5 emissions, their main sources and impacts on human health, environment, climate, air quality, and the reason why PM2.5 emissions from residential wood burning are harmful. Paper also gives an overview of spatial PM2.5 emission distribution in Croatia, their five air quality zones and four agglomerations. The paper analyses the sources and their contribution to PM2.5 emissions with the relevance of PM2.5 emissions from residential plants, the use of fuels in residential plants and their contribution to PM2.5 emissions and PM2.5 emissions by fuel combustion technologies in residential sector. Appropriate strategies, policies, and actions to reduce the impact of residential biomass (wood) burning on the environment, air quality and human health are considered.

scholarly journals Estimating Human Health Impacts and Costs Due to Iranian Fossil Fuel Power Plant Emissions through the Impact Pathway Approach

Energies ◽  
2017 ◽  
Vol 10 (12) ◽  
pp. 2136 ◽  
Author(s):  
Mojtaba Jorli ◽  
Steven Van Passel ◽  
Hossein Sadeghi ◽  
Alireza Nasseri ◽  
Lotfali Agheli
Keyword(s):  
Power Plant ◽  
Human Health ◽  
Fossil Fuel ◽  
Health Impacts ◽  
Power Plant Emissions ◽  
Human Health Impacts ◽  
Fossil Fuel Power Plant ◽  
Impact Pathway ◽  
Plant Emissions ◽  
The Impact

scholarly journals Large air quality and human health impacts due to Amazon forest and vegetation fires

2020 ◽  
Vol 2 (9) ◽  
pp. 095001 ◽  
Author(s):  
Edward W Butt ◽  
Luke Conibear ◽  
Carly L Reddington ◽  
Eoghan Darbyshire ◽  
William T Morgan ◽  
...  
Keyword(s):  
Air Quality ◽  
Human Health ◽  
Health Impacts ◽  
Amazon Forest ◽  
Human Health Impacts ◽  
Vegetation Fires

scholarly journals Special Issue Air Quality and Smoke Management

Atmosphere ◽  
2020 ◽  
Vol 11 (12) ◽  
pp. 1361
Author(s):  
Scott L. Goodrick
Keyword(s):  
Air Quality ◽  
Human Health ◽  
Wildland Fire ◽  
Health Impacts ◽  
Special Issue ◽  
Smoke Management ◽  
Future Studies ◽  
Fire Smoke ◽  
Human Health Impacts

The Atmosphere Special Issue “Special Issue Air Quality and Smoke Management” explores our ability to simulate wildland fire smoke events and the potential to link such modeling to future studies of human health impacts [...]

scholarly journals The regional impact of urban emissions on air quality in Europe: the role of the urban canopy effects

2021 ◽  
Author(s):  
Peter Huszar ◽  
Jan Karlický ◽  
Jana Marková ◽  
Tereza Nováková ◽  
Marina Liaskoni ◽  
...  
Keyword(s):  
Air Quality ◽  
Rural Areas ◽  
Land Surface ◽  
Urban Areas ◽  
Regional Climate ◽  
Regional Scale ◽  
Urban Canopy ◽  
Near Surface ◽  
Urban Emissions ◽  
The Impact

Abstract. Urban areas are hot-spots of intense emissions and they influence air-quality not only locally but on regional or even global scales. The impact of urban emissions over different scales depends on the dilution and chemical transformation of the urban plumes which are governed by the local and regional scale meteorological conditions. These are influenced by the presence of urbanized land-surface via the so called urban canopy meteorological forcing (UCMF). In this study, we investigate for selected central European cities (Berlin, Budapest, Munich, Prague, Vienna and Warsaw), how the urban emission impact (UEI) is modulated by the UCMF for present day climate conditions (2015–2016) using three regional climate-chemistry models: the regional climate models RegCM and WRF-Chem (its meteorological part), the chemistry transport model CAMx coupled to either RegCM and WRF and the “chemical” component of WRF-Chem. The UCMF was calculated by replacing the urbanized surface by rural one while the UEI was estimated by removing all anthropogenic emissions from the selected cities. We analyzed the urban emissions induced changes of near surface concentrations of NO2, O3 and PM2.5. We found increases of NO2 and PM2.5 concentrations over cities by 4–6 ppbv, and 4–6 μgm−3, respectively meaning that about 40–60 % and 20–40 % of urban concentrations of NO2 and PM2.5 are caused by local emissions and the rest is the result of emissions from surrounding rural areas. We showed that if UCMF is included, the UEI of these pollutants is about 40–60 % smaller, or in other words, the urban emission impact is overestimated if urban canopy effects are not taken into account. In case of ozone, models due to UEI usually predict decreases around −2 to −4 ppbv (about 10–20 %), which is again smaller if UCMF is considered (by about 60 %). We further showed that the impact on extreme (95th percentile) air-pollution is much stronger, as well as the modulation of UEI is larger for such situations. Finally, we evaluated the contribution of the urbanization induced modifications of vertical eddy-diffusion to the modulation of UEI, and found that it alone is able to explain the modelled decrease of the urban emission impact if the effects of UCMF are considered. In summary, our results showed that the meteorological changes resulting from urbanization have to be included in regional model studies if they intend to quantify the regional fingerprint of urban emissions. Ignoring these meteorological changes can lead to strong overestimation of UEI.

scholarly journals Air quality and human health impacts of grasslands and shrublands in the United States

2018 ◽  
Vol 182 ◽  
pp. 193-199 ◽  
Author(s):  
Varsha Gopalakrishnan ◽  
Satoshi Hirabayashi ◽  
Guy Ziv ◽  
Bhavik R. Bakshi
Keyword(s):  
United States ◽  
Air Quality ◽  
Human Health ◽  
The United States ◽  
Health Impacts ◽  
Human Health Impacts

scholarly journals Wildfire Smoke Transport and Air Quality Impacts in Different Regions of China

Atmosphere ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 941
Author(s):  
Fengjun Zhao ◽  
Yongqiang Liu ◽  
Lifu Shu ◽  
Qi Zhang
Keyword(s):  
Air Quality ◽  
Human Health ◽  
Northeast China ◽  
Southwest China ◽  
Regional Scale ◽  
Health Impacts ◽  
Fire Emissions ◽  
Wildfire Smoke ◽  
Human Health Impacts ◽  
Smoke Transport

The air quality and human health impacts of wildfires depend on fire, meteorology, and demography. These properties vary substantially from one region to another in China. This study compared smoke from more than a dozen wildfires in Northeast, North, and Southwest China to understand the regional differences in smoke transport and the air quality and human health impacts. Smoke was simulated using the Hybrid Single Particle Lagrangian Integrated Trajectory Model (HYSPLIT) with fire emissions obtained from the Global Fire Emission Database (GFED). Although the simulated PM2.5 concentrations reached unhealthy or more severe levels at regional scale for some largest fires in Northeast China, smoke from only one fire was transported to densely populated areas (population density greater than 100 people/km2). In comparison, the PM2.5 concentrations reached unhealthy level in local densely populated areas for a few fires in North and Southwest China, though they were very low at regional scale. Thus, individual fires with very large sizes in Northeast China had a large amount of emissions but with a small chance to affect air quality in densely populated areas, while those in North and Southwest China had a small amount of emissions but with a certain chance to affect local densely populated areas. The results suggest that the fire and air quality management should focus on the regional air quality and human health impacts of very large fires under southward/southeastward winds toward densely populated areas in Northeast China and local air pollution near fire sites in North and Southwest China.

scholarly journals The Historical Trend of Air Pollution and Its Impact on Human Health in Campania Region (Italy)

Atmosphere ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 553
Author(s):  
Domenico Toscano ◽  
Fabio Murena
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Human Health ◽  
Urban Areas ◽  
Average Concentration ◽  
Special Focus ◽  
Concentration Data ◽  
Limit Values ◽  
Campania Region ◽  
The Impact

The Campania region covers an area of about 13,590 km2 with 5.8 million residents. The area suffers from several environmental issues due to urbanization, the presence of industries, wastewater treatment, and solid waste management concerns. Air pollution is one of the most relevant environmental troubles in the Campania region, frequently exceeding the limit values established by European directives. In this paper, airborne pollutant concentration data measured by the regional air quality network from 2003 to 2019 are collected to individuate the historical trends of nitrogen dioxide (NO2), coarse and fine particulate matter with aerodynamic diameters smaller than 10 μm (PM10) and 2.5 μm (PM2.5), and ozone (O3) through the analysis of the number of exceedances of limit values per year and the annual average concentration. Information on spatial variability and the effect of the receptor category is obtained by lumping together data belonging to the same province or category. To obtain information on the general air quality rather than on single pollutants, the European Air Quality Index (EU-AQI) is also evaluated. A special focus is dedicated to the effect of deep street canyons on air quality, since they are very common in the urban areas in Campania. Finally, the impact of air pollution from 2003 to 2019 on human health is also analyzed using the software AIRQ+.

scholarly journals Influence of air quality model resolution on uncertainty associated with health impacts

2012 ◽  
Vol 12 (6) ◽  
pp. 14525-14549
Author(s):  
T. M. Thompson ◽  
N. E. Selin
Keyword(s):  
Air Quality ◽  
Confidence Interval ◽  
Human Health ◽  
Confidence Intervals ◽  
Health Impacts ◽  
Base Case ◽  
Response Functions ◽  
Model Resolution ◽  
Ozone Concentrations ◽  
The Impact

Abstract. We use regional air quality modeling to evaluate the impact of model resolution on uncertainty associated with the human health benefits resulting from proposed air quality regulations. Using a regional photochemical model (CAMx), we ran a modeling episode with meteorological inputs representing conditions as they occurred during August through September 2006, and two emissions inventories (a 2006 base case and a 2018 proposed control scenario, both for Houston, Texas) at 36, 12, 4 and 2 km resolution. The base case model performance was evaluated for each resolution against daily maximum 8-h averaged ozone measured at monitoring stations. Results from each resolution were more similar to each other than they were to measured values. Population-weighted ozone concentrations were calculated for each resolution and applied to concentration response functions (with 95% confidence intervals) to estimate the health impacts of modeled ozone reduction from the base case to the control scenario. We found that estimated avoided mortalities were not significantly different between 2, 4 and 12 km resolution runs, but 36 km resolution may over-predict some potential health impacts. Given the cost/benefit analysis requirements of the Clean Air Act, the uncertainty associated with human health impacts and therefore the results reported in this study, we conclude that health impacts calculated from population weighted ozone concentrations obtained using regional photochemical models at 36 km resolution fall within the range of values obtained using fine (12 km or finer) resolution modeling. However, in some cases, 36 km resolution may not be fine enough to statistically replicate the results achieved using 2 and 4 km resolution. On average, when modeling at 36 km resolution, 7 deaths per ozone month were avoided because of ozone reductions resulting from the proposed emissions reductions (95% confidence interval was 2–9). When modeling at 2, 4 or 12 km finer scale resolution, on average 5 deaths were avoided due to the same reductions (95% confidence interval was 2–7). Initial results for this specific region show that modeling at a resolution finer than 12 km is unlikely to improve uncertainty in benefits analysis. We suggest that 12 km resolution may be appropriate for uncertainty analyses in areas with similar chemistry, but that resolution requirements should be assessed on a case-by-case basis and revised as confidence intervals for concentration-response functions are updated.

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