Correlation of climatic factors and dengue incidence in Metro Manila, Philippines

Dengue is a serious public health problem in Metro Manila, Philippines. Increasing dengue incidence has been attributed to climate change; however, contradicting reports show inconclusive relationships between dengue and climatic factors. This study investigates temperature and rainfall as climatic factors affecting dengue incidence in Metro Manila from 1996 to 2005. Monthly dengue incidence and climatic data for Metro Manila were collected over a 10-y period (1996-2005). Climatic factors temperature and rainfall were linked with dengue incidence through regression analysis. A predictive model equation plots dengue incidence (Y) versus rainfall (X), which suggests that rainfall is significantly correlated to dengue incidence (r2 = 0.377, p < 0.05). No significant correlation between dengue incidence and temperature was established (p > 0.05). Evidence shows dengue incidence in Metro Manila varies with changing rainfall patterns. Intensified surveillance and control of mosquitoes during periods with high rainfall are recommended.     

Air pollutants and health outcomes: Assessment of confounding by influenza

We assessed confounding of associations between short-term effects of air pollution and health outcomes by influenza using Hong Kong mortality and hospitalization data for 1996–2002.Three measures of influenza were defined: (i) intensity: weekly proportion of positive influenza viruses, (ii) epidemic: weekly number of positive influenza viruses ≥4% of the annual number for ≥2 consecutive weeks, and (iii) predominance: an epidemic period with co-circulation of respiratory syncytial virus <2% of the annual positive isolates for ≥2 consecutive weeks. We examined effects of influenza on associations between nitrogen dioxide (NO₂), sulfur dioxide (SO₂), particulate matter with aerodynamic diameter ≤10 μm (PM₁₀) and ozone (O₃) and health outcomes including all natural causes mortality, cardiorespiratory mortality and hospitalization. Generalized additive Poisson regression model with natural cubic splines was fitted to control for time-varying covariates to estimate air pollution health effects. Confounding with influenza was assessed using an absolute difference of >0.1% between unadjusted and adjusted excess risks (ER%).Without adjustment, pollutants were associated with positive ER% for all health outcomes except asthma and stroke hospitalization with SO₂ and stroke hospitalization with O₃. Following adjustment, changes in ER% for all pollutants were <0.1% for all natural causes mortality, but >0.1% for mortality from stroke with NO₂ and SO₂, cardiac or heart disease with NO₂, PM₁₀ and O₃, lower respiratory infections with NO₂ and O₃ and mortality from chronic obstructive pulmonary disease with all pollutants. Changes >0.1% were seen for acute respiratory disease hospitalization with NO₂, SO₂ and O₃ and acute lower respiratory infections hospitalization with PM₁₀. Generally, influenza does not confound the observed associations of air pollutants with all natural causes mortality and cardiovascular hospitalization, but for some pollutants and subgroups of cardiorespiratory mortality and respiratory hospitalization there was evidence to suggest confounding by influenza.     

Optical and thermal characteristics of carbonaceous aerosols measured at an urban site in Gwangju,Korea, in the winter of 2011

Carbonaceous components (organic carbon [OC] and elemental carbon [EC]) and optical properties (light absorption and scattering) of fine particulate matter (aerodynamic diameter <2.5 μm; PM_2.5) were simultaneously measured at an urban site in Gwangju, Korea, during the winter of 2011. OC was further classified into OC1, OC2, OC3, and OC4, based on a temperature protocol using a Sunset OC/EC analyzer. The average OC and EC concentrations were 5.0 ± 2.5 and 1.7 ± 0.9 μg C m^?3, respectively. The average single-scattering albedo (SSA) at a wavelength of 550 nm was 0.58 ± 0.11, suggesting that the aerosols observed in the winter of 2011 had a local warming effect in this area. During the whole sampling period, “stagnant PM” and “long-range transport PM” events were identified. The light absorption coefficient (b_abs) was higher during the stagnant PM event than during the long-range transport PM event due to the existence of abundant light-absorbing OC during the stagnant PM event. In particular, the OC2 and OC3 concentrations were higher during the stagnant PM event than those during the long-range transport event, suggesting that OC2 and OC3 might be more related to the light-absorbing OC. The light scattering coefficient (b_scat) was similar between the events. On average, the mass absorption efficiency attributed to EC (σ_EC) was 9.6 m² g^?1, whereas the efficiency attributed to OC (σ_OC) was 1.8 m² g^?1 at λ = 550 nm. Furthermore, the σ_EC is comparable among the PM event days, but the σ_OC for the stagnant PM event was significantly higher than that for the long-range transport PM event (1.7 vs. 0.5).

Implications: Optical and thermal properties of carbonaceous aerosol were measured at Gwangju, and carbonaceous aerosol concentration and optical property varied between “stagnant PM” and “long-range transport PM” events. More abundant light absorbing OC was observed during the stagnant PM event.     

Photochemical model performance for PM2.5 sulfate,nitrate, ammonium,and precursor species SO2, HNO3, and NH3 at background monitor locations in the central and eastern United States

Health studies have shown premature death is statistically associated with exposure to particulate matter <2.5 μm in diameter (PM2.5). The United States Environmental Protection Agency requires all States with PM2.5 non-attainment counties or with sources contributing to visibility impairment at Class I areas to submit an emissions control plan. These emission control plans will likely focus on reducing emissions of sulfur oxides and nitrogen oxides, which form two of the largest chemical components of PM2.5 in the eastern United States: ammonium sulfate and ammonium nitrate. Emission control strategies are simulated using three-dimensional Eulerian photochemical transport models.A monitor study was established using one urban (Detroit) and nine rural locations in the central and eastern United States to simultaneously measure PM2.5 sulfate ion (SO₄²⁻), nitrate ion (NO₃⁻), ammonium ion (NH₄⁺), and precursor species sulfur dioxide (SO₂), nitric acid (HNO₃), and ammonia (NH₃). This monitor study provides a unique opportunity to assess how well the modeling system predicts the spatial and temporal variability of important precursor species and co-located PM2.5 ions, which is not well characterized in the central and eastern United States.The modeling system performs well at estimating the PM2.5 species, but does not perform quite as well for the precursor species. Ammonia is under-predicted in the coldest months, nitric acid tends to be over-predicted in the summer months, and sulfur dioxide appears to be systematically over-predicted. Several indicators of PM2.5 ammonium sulfate and ammonium nitrate formation and chemical composition are estimated with the ambient data and photochemical model output. PM2.5 sulfate ion is usually not fully neutralized to ammonium sulfate in ambient measurements and is usually fully neutralized in model estimates. The model and ambient estimates agree that the ammonia study monitors tend to be nitric acid limited for PM2.5 nitrate formation. Regulatory strategies in this part of the country should focus on reductions in NO_X rather than ammonia to control PM2.5 ammonium nitrate.     

Combined effects of elevated CO2 and natural climatic variation on leaf spot diseases of redbud and sweetgum trees

Atmospheric CO₂ concentrations are predicted to double within the next century and alter climate regimes, yet the extent that these changes will affect plant diseases remains unclear. In this study conducted over five years, we assessed how elevated CO₂ and interannual climatic variability affect Cercospora leaf spot diseases of two deciduous trees. Climatic data varied considerably between the five years and altered disease expression. Disease incidence and severity for both species were greater in years with above average rainfall. In years with above average temperatures, disease incidence for Liquidambar styraciflua was decreased significantly. When significant changes did occur, disease incidence and severity always increased under elevated CO₂. Chlorophyll fluorescence imaging of leaves revealed that any visible increase in disease severity induced by elevated CO₂ was mitigated by higher photosynthetic efficiency in the remaining undamaged leaf tissue and in a halo surrounding lesions.     

Daily Mortality and Air Pollution in the Netherlands

ABSTRACT

We studied the association of daily mortality with short-term variations in the ambient concentrations of major gaseous pollutants and PM in the Netherlands. The magnitude of the association in the four major urban areas was compared with that in the remainder of the country. Daily cause-specific mortality counts, air quality, temperature, relative humidity, and influenza data were obtained from 1986 to 1994. The relationship between daily mortality and air pollution was modeled using Poisson regression analysis. We adjusted for potential confounding due to long-term and seasonal trends, influenza epidemics, ambient temperature and relative humidity, day of the week, and holidays, using generalized additive models.

Influenza episodes were associated with increased mortality up to 3 weeks later. Daily mortality was significantly associated with the concentration of all air pollutants. An increase in the PM₁₀ concentration by 100 u.g/m³ was associated with a relative risk (RR) of 1.02 for total mortality. The largest RRs were found for pneumonia deaths. Ozone had the most consistent, independent association with mortality. Particulate air pollution (e.g., PM₁₀, black smoke [BS]) was not more consistently associated with mortality than were the gaseous pollutants SO₂ and NO₂. Aerosol SO₄ ^-2, NO₃ ^-, and BS were more consistently associated with total mortality than was PM₁₀. The RRs for all pollutants were substantially larger in the summer months than in the winter months. The RR of total mortality for PM₁₀ was 1.10 for the summer and 1.03 for the winter. There was no consistent difference between RRs in the four major urban areas and the more rural areas.     

Defining the Photochemical Contribution to Particulate Matter in Urban Areas Using Time-Series Analysis

Abstract

The objective of this project is to demonstrate how the ambient air measurement record can be used to define the relationship between O₃ (as a surrogate for photochemistry) and secondary particulate matter (PM) in urban air. The approach used is to develop a time-series transfer-function model describing the daily PM₁₀ (PM with less than 10 μm aerodynamic diameter) concentration as a function of lagged PM and current and lagged O₃, NO or NO₂, CO, and SO₂. Approximately 3 years of daily average PM₁₀, daily maximum 8-hr average O₃ and CO, daily 24-hr average SO₂ and NO₂, and daily 6:00 a.m.-9:00 a.m. average NO from the Aerometric Information Retrieval System (AIRS) air quality subsystem are used for this analysis. Urban areas modeled are Chicago, IL; Los Angeles, CA; Phoenix, AZ; Philadelphia, PA; Sacramento, CA; and Detroit, MI. Time-series analysis identified significant autocorrelation in the O₃, PM₁₀, NO, NO₂,CO, and SO₂ series. Cross correlations between PM₁₀ (dependent variable) and gaseous pollutants (independent variables) show that all of the gases are significantly correlated with PM₁₀ and that O₃ is also significantly correlated lagged up to two previous days. Once a transfer-function model of current PM₁₀ is defined for an urban location, the effect of an O₃-control strategy on PM concentrations is estimated by calculating daily PM₁₀ concentrations with reduced O₃ concentrations. Forecasted summertime PM₁₀ reductions resulting from a 5 percent decrease in ambient O₃ range from 1.2 μg/m³ (3.03%) in Chicago to 3.9 μg/m³ (7.65%) in Phoenix.     

Response of Fine Particulate Matter to Emission Changes of Oxides of Nitrogen and Anthropogenic Volatile Organic Compounds in the Eastern United States

Abstract

A three-dimensional chemical transport model (Particulate Matter Comprehensive Air Quality Model with Extensions [PMCAMx]) is used to investigate changes in fine particle (PM_2.5) concentrations in response to 50% emissions changes of oxides of nitrogen (NO_x) and anthropogenic volatile organic compounds (VOCs) during July 2001 and January 2002 in the eastern United States. The reduction of NO_x emissions by 50% during the summer results in lower average oxidant levels and lowers PM_2.5 (8% on average), mainly because of reductions of sulfate (9–11%), nitrate (45–58%), and ammonium (7–11%). The organic particulate matter (PM) slightly decreases in rural areas, whereas it increases in cities by a few percent when NO_x is reduced. Reduction of NO_x during winter causes an increase of the oxidant levels and a rather complicated response of the PM components, leading to small net changes. Sulfate increases (8–17%), nitrate decreases (18– 42%), organic PM slightly increases, and ammonium either increases or decreases a little. The reduction of VOC emissions during the summer causes on average a small increase of the oxidant levels and a marginal increase in PM_2.5. This small net change is due to increases in the inorganic components and decreases of the organic ones. Reduction of VOC emissions during winter results in a decrease of the oxidant levels and a 5–10% reduction of PM_2.5 because of reductions in nitrate (4–19%), ammonium (4–10%), organic PM (12–14%), and small reductions in sulfate. Although sulfur dioxide (SO₂) reduction is the single most effective approach for sulfate control, the coupled decrease of SO₂ and NO_x emissions in both seasons is more effective in reducing total PM_2.5 mass than the SO₂ reduction alone.     

Time-Series Analysis of Above-Road Particulate Matter at the Caldecott Tunnel Exit

ABSTRACT

On November 18, 1997, above-road particulate matter (PM) lidar (light detection and ranging) signals and heavy-duty (HD) and light-duty (LD) vehicle counts were simultaneously collected for 894 10-sec sampling periods at the Caldecott Tunnel in Orinda, CA, for the purpose of measuring the relative contributions of LD and HD vehicles to the PM lidar signal under real-world driving conditions. The relationship between the PM lidar signal and traffic activity (i.e., LD and HD traffic volumes) was examined using a time-series analysis technique, multilagged regression. The time-series model results indicate that the PM lidar signal in the current sampling period (PM_t) depended on the level recorded in the previous three sampling periods (i.e., PM_t-1, PM_t-2, and PM_t-3), the number of LD vehicles in the seventh past sampling period (LD_t-7), and the number of HD vehicles measured 80 sec previous to the current sampling period (HD_t-8). On a 10-sec period basis, the model results indicate that HD vehicles contributed, on average, 3 times more to above-road PM li-dar signals than did LD vehicles. The observed lag in the relationship between vehicle types and the lidar signal 20 m above the road suggests that resuspended road dust, rather than tailpipe exhaust emissions, was the main source of the detected PM. Detection of road dust at such heights above the road suggests the need for investigating the processes governing the vertical transport and recycling of PM over the road as a function of vehicle dynamics under a range of meteorological conditions.     

Effect of global climatic change on carbonation progress of concrete

In the recent years, global warming has dramatically increased the atmospheric carbon-dioxide (CO₂) concentration and temperature. As a consequence of this, carbonation has become one of the most critical durability issues for concrete structures in urban environment.In this study, the climate scenario IS92a recommended by Intergovernmental Panel on Climate Change (IPCC) is used for evaluating the effect of CO₂ concentration on carbonation of concrete. A modified mathematical equation, based on Fick's 1st law of diffusion, is used to evaluate CO₂ diffusion coefficient of concrete. The required cover depth of concrete is estimated by using the applicative methods of reliability and stochastic concepts to take microclimatic conditions into consideration.The tolerance of cover depth should be considered in order to prevent carbonation-induced corrosion. From the relationship between the weight loss of reinforcement and corrosion current density for a given time, the tolerance of cover depth to prevent carbonation-induced corrosion is suggested. It was observed that corrosion occurs when the distance between carbonation front and reinforcement bar surface (the uncarbonated depth) is <5 mm.     

Modeling wintertime particulate matter formation in central California

A wintertime episode during the 2000 California Regional PM Air Quality Study (CRPAQS) was simulated with the air quality model CMAQ–MADRID. Model performance was evaluated with 24-h average measurements available from CRPAQS. Modeled organic matter (OM) was dominated by emissions, which were probably significantly under-represented, especially in urban areas. In one urban area, modeled daytime nitrate concentrations were low and evening concentrations were high. This diurnal profile was not explained by the partition of nitrate between the gas and particle phases, because gaseous nitric acid concentrations were low compared to PM nitrate. Both measured and simulated nitrate concentrations aloft were lower than at the surface at two tower locations during this episode. Heterogeneous reactions involving NO₃ and N₂O₅ accounted for significant nitrate production in the model, resulting in a nighttime peak. The sensitivity of PM nitrate to precursor emissions varied with time and space. Nitrate formation was on average sensitive to NO_x emissions. However, for some periods at urban locations, reductions in NO_x caused the contrary response of nitrate increases. Nitrate was only weakly sensitive to reductions in anthropogenic VOC emissions. Nitrate formation tended to be insensitive to the availability of ammonia at locations with high nitrate, although the spatial extent of the nitrate plume was reduced when ammonia was reduced. Reductions in PM emissions caused OM to decrease, but had no effect on nitrate despite the role of heterogeneous reactions. A control strategy that focuses on NO_x and PM emissions would be effective on average, but reductions in VOC and NH₃ emissions would also be beneficial for certain times and locations.     

PM composition and source reconciliation in Mexico City

PM_2.5 and PM₁₀ were collected during 24-h sampling intervals from March 1st to 31st, 2006 during the MILAGRO campaign carried out in Mexico City's northern region, in order to determine their chemical composition, oxidative activity and the estimation of the source contributions during the sampling period by means of the chemical mass balance (CMB) receptor model. PM_2.5 concentrations ranged from 32 to 70 μg m⁻³ while that of PM10 did so from 51 to 132 μg m⁻³. The most abundant chemical species for both PM fractions were: OC, EC, SO₄²⁻, NO₃⁻, NH₄⁺, Si, Fe and Ca. The majority of the PM mass was comprised of carbon, up to about 52% and 30% of the PM2.5 and PM10, respectively. PM2.5 constituted more than 50% of PM10. The redox activity, assessed by the dithiothreitol (DTT) assay, was greater for PM_2.5 than for PM₁₀, and did not display significant differences during the sampling period. The PM_2.5 source reconciliation showed that in average, vehicle exhaust emissions were its most important source in an urban site with a 42% contribution, followed by re-suspended dust with 26%, secondary inorganic aerosols with 11%, and industrial emissions and food cooking with 10% each. These results had a good agreement with the Emission Inventory. In average, the greater mass concentration occurred during O₃S that corresponds to a wind shift initially with transport to the South but moving back to the North. Taken together these results show that PM chemical composition, oxidative potential, and source contribution is influenced by the meteorological conditions.     

Extended effects of air pollution on cardiopulmonary mortality in Vienna

BackgroundCurrent standards for fine particulates and nitrogen dioxide are under revision. Patients with cardiovascular disease have been identified as the largest group which need to be protected from effects of urban air pollution.MethodsWe sought to estimate associations between indicators of urban air pollution and daily mortality using time series of daily TSP, PM₁₀, PM_2.5, NO₂, SO₂, O₃ and nontrauma deaths in Vienna (Austria) 2000–2004. We used polynomial distributed lag analysis adjusted for seasonality, daily temperature, relative humidity, atmospheric pressure and incidence of influenza as registered by sentinels.ResultsAll three particulate measures and NO₂ were associated with mortality from all causes and from ischemic heart disease and COPD at all ages and in the elderly. The magnitude of the effect was largest for PM_2.5 and NO₂. Best predictor of mortality increase lagged 0–7 days was PM_2.5 (for ischemic heart disease and COPD) and NO₂ (for other heart disease and all causes). Total mortality increase, lagged 0–14 days, per 10 μg m⁻³ was 2.6% for PM_2.5 and 2.9% for NO₂, mainly due to cardiopulmonary and cerebrovascular causes.ConclusionAcute and subacute lethal effects of urban air pollution are predicted by PM_2.5 and NO₂ increase even at relatively low levels of these pollutants. This is consistent with results on hospital admissions and the lack of a threshold. While harvesting (reduction of mortality after short increase due to premature deaths of most sensitive persons) seems to be of minor importance, deaths accumulate during 14 days after an increase of air pollutants. The limit values for PM_2.5 and NO₂ proposed for 2010 in the European Union are unable to prevent serious health effects.     

The impact of CO2 capture in the power and heat sector on the emission of SO2, NOx,particulate matter,volatile organic compounds and NH3 in the European Union

This study quantifies the trade-offs and synergies between climate and air quality policy objectives for the European power and heat (P&H) sector. An overview is presented of the expected performance data of CO₂ capture systems implemented at P&H plants, and the expected emission of key air pollutants, being: SO₂, NO_X, NH₃, volatile organic compounds (VOCs) and particulate matter (PM). The CO₂ capture systems investigated include: post-combustion, oxyfuel combustion and pre-combustion capture.For all capture systems it was found that SO₂, NO_x and PM emissions are expected to be reduced or remain equal per unit of primary energy input compared to power plants without CO₂ capture. Increase in primary energy input as a result of the energy penalty for CO₂ capture may for some technologies and substances result in a net increase of emissions per kWh output. The emission of ammonia may increase by a factor of up to 45 per unit of primary energy input for post-combustion technologies. No data are available about the emission of VOCs from CO₂ capture technologies.A simple model was developed and applied to analyse the impact of CO₂ capture in the European P&H sector on the emission level of key air pollutants in 2030. Four scenarios were developed: one without CO₂ capture and three with one dominantly implemented CO₂ capture system, varying between: post-combustion, oxyfuel combustion and pre-combustion.The results showed a reduction in GHG emissions for the scenarios with CO₂ capture compared to the baseline scenario between 12% and 20% in the EU 27 region in 2030. NO_x emissions were 15% higher in the P&H sector in a scenario with predominantly post-combustion and lower when oxyfuel combustion (?16%) or pre-combustion (?20%) were implemented on a large scale. Large scale implementation of the post-combustion technology in 2030 may also result in significantly higher, i.e. increase by a factor of 28, NH₃ emissions compared to scenarios with other CO₂ capture options or without capture. SO₂ emissions were very low for all scenarios that include large scale implementation of CO₂ capture in 2030, i.e. a reduction varying between 27% and 41%. Particulate Matter emissions were found to be lower in the scenarios with CO₂ capture. The scenario with implementation of the oxyfuel technology showed the lowest PM emissions followed by the scenario with a significant share allocated to pre-combustion, respectively ?59% and ?31%. The scenario with post-combustion capture resulted in PM emissions varying between 35% reduction and 26% increase.     

Idle Emissions from Heavy-Duty Diesel Vehicles: Review and Recent Data

Abstract

Heavy-duty diesel vehicle idling consumes fuel and reduces atmospheric quality, but its restriction cannot simply be proscribed, because cab heat or air-conditioning provides essential driver comfort. A comprehensive tailpipe emissions database to describe idling impacts is not yet available. This paper presents a substantial data set that incorporates results from the West Virginia University transient engine test cell, the E-55/59 Study and the Gasoline/Diesel PM Split Study. It covered 75 heavy-duty diesel engines and trucks, which were divided into two groups: vehicles with mechanical fuel injection (MFI) and vehicles with electronic fuel injection (EFI). Idle emissions of CO, hydrocarbon (HC), oxides of nitrogen (NO_x), particulate matter (PM), and carbon dioxide (CO₂) have been reported. Idle CO₂ emissions allowed the projection of fuel consumption during idling. Test-to-test variations were observed for repeat idle tests on the same vehicle because of measurement variation, accessory loads, and ambient conditions. Vehicles fitted with EFI, on average, emitted [~20 g/hr of CO, 6 g/hr of HC, 86 g/hr of NO_x, 1 g/hr of PM, and 4636 g/hr of CO₂ during idle. MFI equipped vehicles emitted ~35 g/hr of CO, 23 g/hr of HC, 48 g/hr of NO_x, 4 g/hr of PM, and 4484 g/hr of CO₂, on average, during idle. Vehicles with EFI emitted less idleCO, HC, and PM, which could be attributed to the efficient combustion and superior fuel atomization in EFI systems. Idle NO_x, however, increased with EFI, which corresponds with the advancing of timing to improve idle combustion. Fuel injection management did not have any effect on CO₂ and, hence, fuel consumption. Use of air conditioning without increasing engine speed increased idle CO₂, NO_x, PM, HC, and fuel consumption by 25% on average. When the engine speed was elevated from 600 to 1100 revolutions per minute, CO₂ and NO_x emissions and fuel consumption increased by >150%, whereas PM and HC emissions increased by ~100% and 70%, respectively. Six Detroit Diesel Corp. (DDC) Series 60 engines in engine test cell were found to emit less CO, NO_x, and PM emissions and consumed fuel at only 75%of the level found in the chassis dynamometer data. This is because fan and compressor loads were absent in the engine test cell.     

The sensitivity of the CHIMERE model to emissions reduction scenarios on air quality in Northern Italy

The sensitivity of the CHIMERE model to emission reduction scenarios on particulate matter PM2.5 and ozone (O₃) in Northern Italy is studied. The emissions of NO_x, PM2.5 SO₂, VOC or NH₃ were reduced by 50% for different source sectors for the Lombardy region, together with 5 additional scenarios to estimate the effect of local measures on improving the air quality for the Po valley area. Firstly, we evaluate the model performance by comparing calculated surface aerosol concentrations for the standard case (no emission reductions) with observations for January and June 2005. Calculated monthly mean PM10 concentrations are in general underestimated. For June, modelled PM10 concentrations slightly overestimate the measurements. Calculated monthly mean SO₄, NO₃^?, NH₄⁺ concentrations are in good agreement with the observations for January and June. Secondly, the model sensitivity of emission reduction scenarios on PM2.5 and O₃ calculated concentrations for the Po valley area is evaluated. The most effective scenarios to abate PM2.5 concentration are based on the SNAP2 (non-industrial combustion plants) and SNAP7 (road traffic) sectors, for which the NO_x and PM2.5 emissions are reduced by 50%. The number of days that the 2015 PM2.5 limit value of 25 μg m^?3 in Milan is exceeded by reducing primary PM2.5 and NO_x emissions for SNAP2 and 7 by 50%, does not change in January when compared to the standard case for the Milan area. It appears that 40% of the PM2.5 concentration in the greater Milan area is caused by the emissions surrounding the Lombardy region and from the model boundary conditions.This study also showed that a more effective pollutant reduction (emissions) per ton of pollutant reduced (concentrations) for the greater Milan area is obtained by reducing the primary PM2.5 emissions for SNAP7 by 50%. The most effective scenario on PM2.5 decrease for which precursor emissions are reduced is achieved by reducing SO₂ emissions by 50% for SNAP7.Our study showed that during summer time, the largest reductions in O₃ concentrations are achieved for SNAP7 emission reductions, when volatile organic compounds (VOCs) are reduced by 50%.     

Positive effects of vegetation: urban heat island and green roofs

This paper attempts to evaluate the positive effects of vegetation with a multi-scale approach: an urban and a building scale.Monitoring the urban heat island in four areas of New York City, we have found an average of 2 °C difference of temperatures between the most and the least vegetated areas, ascribable to the substitution of vegetation with man-made building materials.At micro-scale, we have assessed the effect of surface albedo on climate through the use of a climatological model. Then, using the CO₂ equivalents as indicators of the impact on climate, we have compared the surface albedo, and the construction, replacement and use phase of a black, a white and a green roof. By our analyses, we found that both the white and the green roofs are less impactive than the black one; with the thermal resistance, the biological activity of plants and the surface albedo playing a crucial role.     

Day-of-Week Patterns of Particulate Matter and Its Chemical Components at Selected Sites in California

Abstract

This paper analyzes day-of-week variations in concentrations of particulate matter (PM) in California. Because volatile organic compounds (VOCs) and oxides of nitrogen (NO_x) are not only precursors of ozone (O₃) but also of secondary PM, it is useful to know whether the variations by day of week in these precursors are also evident in PM data. Concentrations of PM ≤10 μm (PM₁₀) and ≤2.5[H9262]m in aerodynamic diameter (PM_2.5) were analyzed. PM concentrations exhibit a general weekly pattern, with the maximum occurring late in the workweek and the minimum occurring on weekends (especially Sunday); however, this pattern does not prevail at all sites and areas. PM nitrate (NO₃ ^-) data from Size Selective Inlet (SSI) samplers in the South Coast Air Basin (SoCAB) tend to be somewhat lower on weekends compared with weekdays. During 1988–1991, the weekend average was lower than the weekday average at 8 of 13 locations, with an average decrease of 1%. During 1997–2000, the weekend average was lower than the weekday average at 10 of 13 locations, with an average decrease of 6%. The weekend averages are generally lower than weekday averages for sulfates, organic carbon, and elemental carbon. Because heavy-duty trucks typically represent a major source of elemental carbon, the weekend decrease in heavy-duty truck traffic may also result in a decrease in ambient elemental carbon concentrations.     

Feasibility of using low-cost portable particle monitors for measurement of fine and coarse particulate matter in urban ambient air

Exposure to ambient particulate matter (PM) is known as a significant risk factor for mortality and morbidity due to cardiorespiratory causes. Owing to increased interest in assessing personal and community exposures to PM, we evaluated the feasibility of employing a low-cost portable direct-reading instrument for measurement of ambient air PM exposure. A Dylos DC 1700 PM sensor was collocated with a Grimm 11-R in an urban residential area of Houston Texas. The 1-min averages of particle number concentrations for sizes between 0.5 and 2.5 µm (small size) and sizes larger than 2.5 µm (large size) from a DC 1700 were compared with the 1-min averages of PM_2.5 (aerodynamic size less than 2.5 µm) and coarse PM (aerodynamic size between 2.5 and 10 µm) concentrations from a Grimm 11-R. We used a linear regression equation to convert DC 1700 number concentrations to mass concentrations, utilizing measurements from the Grimm 11-R. The estimated average DC 1700 PM_2.5 concentration (13.2 ± 13.7 µg/m³) was similar to the average measured Grimm 11-R PM_2.5 concentration (11.3 ± 15.1 µg/m³). The overall correlation (r²) for PM_2.5 between the DC 1700 and Grimm 11-R was 0.778. The estimated average coarse PM concentration from the DC 1700 (5.6 ± 12.1 µg/m³) was also similar to that measured with the Grimm 11-R (4.8 ± 16.5 µg/m³) with an r² of 0.481. The effects of relative humidity and particle size on the association between the DC 1700 and the Grimm 11-R results were also examined. The calculated PM mass concentrations from the DC 1700 were close to those measured with the Grimm 11-R when relative humidity was less than 60% for both PM_2.5 and coarse PM. Particle size distribution was more important for the association of coarse PM between the DC 1700 and Grimm 11-R than it was for PM_2.5.

Implications: The performance of a low-cost particulate matter (PM) sensor was evaluated in an urban residential area. Both PM_2.5 and coarse PM (PM_10-2.5) mass concentrations were estimated using a DC1700 PM sensor. The calculated PM mass concentrations from the number concentrations of DC 1700 were close to those measured with the Grimm 11-R when relative humidity was less than 60% for both PM_2.5 and coarse PM. Particle size distribution was more important for the association of coarse PM between the DC 1700 and Grimm 11-R than it was for PM_2.5.