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A Methodology of Assessment of Air Pollution Health Impact Based on Structural Longitudinal Modeling of Hierarchical Systems and Fuzzy Algorithm: Application to Study of Children Respiratory Functions

Friger, M; Bolotin, A; Peleg, R

Ben-Gurion University Of The Negev, Beersheba.

Introduction:

Assessing the effects of air-pollution is a significant problem in the field of modern environmental epidemiology. When modeling these effects it is important that the models must be epidemiologically meaningful and robust (that is, insensitive to variations in the model parameters). The objective of this paper is to propose a methodology for the assessment of the health impact of air pollution. The proposed methodology involves the construction of models for complex dynamic hierarchical systems in environmental epidemiology and their problem-oriented interpretation.

The principal stages of the proposed methodology are:

• Creation of a multivariate hierarchical structural model based on system analysis.
• Generation of a mathematical formalization for this model.
• Development of a statistical model for a particular study case based on the mathematical formalization, using the generalized estimating equations technique and time-series analysis. At this stage, for a dichotomized dependent variable, a special fuzzy algorithm was used. The algorithm employed fuzzy membership functions instead of the binary variable to obtain robust regression models.
• Use of the “multi-layered” approach for model interpretation developed by the authors. This approach involved the creation of special functional time-dependent coefficients that reflect the effect of air pollutants at a given time. These coefficients allow an epidemiological meaningful model interpretation. Thus, they can be used for air-pollution health effects assessment.

The proposed methodology was used to analyze data collected from lung function measurements in 165 children from February-September 2002 (about 4000 individual daily records). The subject variables were age, gender, body-mass index, and place of residency. The meteorological variables included daily maximum temperature, average humidity and barometric pressure. The air-pollutant variables were suspended particles, ozone, nitrogen and sulphur oxides. In addition, the effects were studied up to a 3-day lag. The results demonstrated a statistically significant effect of air-pollution on lung function. Changes in most of the pollutants did not cause a critical decrease in lung function. However, for the observed period, a 10 mkg/m 3 increase in ozone was associated with a mean decrease in lung function of 6 units for a one-day delay.

Discussion and Conclusions:

The assessment of the health effects of air pollution and their interpretation make epidemiological sense, lending support to the correctness of the proposed methodology. Testing the models by changing the dichotomization cutoff for the lung function variability shows that the models based on the proposed fuzzy algorithm are robust.

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A review of urban air pollution monitoring and exposure assessment methods.

1. Introduction

2. monitoring data acquisition, 3. pollution assessment methods, 3.1. spatial interpolation approaches, 3.1.1. inverse distance weighting, 3.1.2. kriging, 3.1.3. data driven spatial prediction, 3.2. land-use regression models, 3.3. dispersion models, 3.4. approaches for mobile monitoring, 3.5. air quality indicators, 4. conclusions, acknowledgments, author contributions, conflicts of interest.

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Xie, X.; Semanjski, I.; Gautama, S.; Tsiligianni, E.; Deligiannis, N.; Rajan, R.T.; Pasveer, F.; Philips, W. A Review of Urban Air Pollution Monitoring and Exposure Assessment Methods. ISPRS Int. J. Geo-Inf. 2017 , 6 , 389. https://doi.org/10.3390/ijgi6120389

Xie X, Semanjski I, Gautama S, Tsiligianni E, Deligiannis N, Rajan RT, Pasveer F, Philips W. A Review of Urban Air Pollution Monitoring and Exposure Assessment Methods. ISPRS International Journal of Geo-Information . 2017; 6(12):389. https://doi.org/10.3390/ijgi6120389

Xie, Xingzhe, Ivana Semanjski, Sidharta Gautama, Evaggelia Tsiligianni, Nikos Deligiannis, Raj Thilak Rajan, Frank Pasveer, and Wilfried Philips. 2017. "A Review of Urban Air Pollution Monitoring and Exposure Assessment Methods" ISPRS International Journal of Geo-Information 6, no. 12: 389. https://doi.org/10.3390/ijgi6120389

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• Published: 15 January 2020

A methodology for the design of an effective air quality monitoring network in port areas

• Luigia Mocerino 1 ,
• Fabio Murena 2 ,
• Franco Quaranta   ORCID: orcid.org/0000-0001-8150-8356 1 &
• Domenico Toscano 2  

Scientific Reports volume  10 , Article number:  300 ( 2020 ) Cite this article

4746 Accesses

24 Citations

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• Environmental impact
• Mechanical engineering

The assessment of the impact of ship emissions is generally realised by a network of receptors at ground level inside the port area or in the nearby urban canopy. Another possibility is the use of dispersion models capable of providing maps of concentrations to the ground taking into account ship emissions and weather conditions. In this work traffic data of passengers ships in the port of Naples were used to estimate pollutant emissions starting from EMEP/EEA (European Environment Agency/European Monitoring and Evaluation Programme) methodology and real data of power engines. In this way, a hourly file of emission rates was produced and input to CALPUFF together with meteorological data. Then SO 2 concentrations at different heights (0–60 m) in correspondence of selected points within the port area were evaluated. Results are compared with data measured at ground level in monitoring campaigns showing how is possible to better identify and quantify the air pollution from ships in port by positioning the receptors inside the port area at different heights from ground-level. The results obtained give useful information for designing an optimum on-site air quality monitoring network able to quantify the emissions of pollutants due to naval traffic and to individuate the contribution of single ships or ships’ categories.

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Introduction.

The effects of pollution connected to ship traffic have impact on a global scale, with the production of greenhouse gases, and on a local scale with the introduction of nitrogen oxides (NO x ), sulfur oxides (SO x ) and particulate matter into the atmosphere. The overall production of pollutants in the lower parts of the atmosphere contributes negatively to the quality of the air we breathe with effects on man and environment. Mainly, SO x are emitted as a function of the content of sulphur in the fuel; the quantity of NO x in the exhausts depends on the inner parameters of engines and on the temperature of combustion, timing. In addition, diesel engines emit particulate matter (PM) mostly during transient states of engines in port and these substances are particularly dangerous since they can create the conditions for oncological diseases.

Ships of any type are “producers” of noxious emissions; in fact, the most part of ships has diesel engines to provide the power needed for the propulsion and for the auxiliary services onboard. However, in all cases, engines must be considered a source of pollution since their operations will cause emissions of noxious elements for sure. The “ International Convention on the Prevention of Pollution from Ships ”, MARPOL ( MARine POLlution ) 73/78, is the IMO ( International Maritime Organization ) regulation concerning ship-related pollution 1 .The Annex VI (1997), of the MARPOL, sets limits on NO x and SO x emissions from ship exhausts and prohibits deliberate emissions of ozone from ships of 400 gross tonnage and above. The original annex of MARPOL has undergone successive modifications aimed at reducing the limits related to the emissions of main pollutants in light of the technological improvements made over the years and the ever more stringent need to reduce emissions 2 , 3 . The main amendment to the regulation saws a progressive reduction in emissions of nitrogen oxide and sulfur and the introduction of controlled emission zones (ECAs) with even more stringent limits 3 . For the NOx emissions, different limits (TIER) have been introduced depending on the year of construction of the ship, the rpm of the engine and the areas where the ship works 3 . To date, the level of reference is TIER II; the TIER III is to be considered valid only in the ECA ( Emission Control Area ) areas 2 . Since the sulphur generating the oxides is present in the fuel (and not in the air as the nitrogen), the limits to the emissions of sulphur oxides concern the mass percentages of sulphur present in the bunkered fuel. From 1 January 2020, the global sulphur cap will be reduced from the actual 3.5% to 0.5% while in the ECA areas; today some zones have a limit of 0.10% (from 1/1/2015) (IMO, 2007).

Many studies concern the assessment of the contribution of ship emissions on air quality in port and nearby urban areas; in several cases a limited contribution of ship emissions inside the port areas is reported. In fact, a large contribution of cruise ship emissions in Victoria’s port (Canada) is observed at about 1 km from the mooring points 4 and up to 5 km inland at Taranto (Italy) 5 . The highest impact of ship emissions of PM 2.5 is estimated at 10 km from the coastline in Bohain Rim region (China) 6 and at about 1 km from the port source in Los Angeles 7 . It is also generally highlighted that the influence of ship emissions on pollutant concentration at ground is statistically relevant only during ship-plume-influenced periods (i.e.; when ship activities occur in correspondence of wind blowing from the port area to the receptor site). This finding comes from measurements of O 3 , NOx, SO 2 and PM 2.5 in Brindisi 8 , of PM 2.5 in Shangai 9 , in Bohain Rim region 6 and in Los Angeles 7 and, finally, of SO 2 in Victoria (Canada) 4 . Results indicate that ships can contribute to 20–30% of the total PM 2.5 but only during ship-plume-influenced periods 9 , and about 11% at 10 km from the coastline. The strong time and wind dependence of the impact of ship emissions at ground level is the reason why some correlation studies use short averaging time measures (from 1 to 10 minutes) 10 , 11 . On the contrary, other studies estimate a significant contribution/impact inside the port area. Yau et al . 12 in Hong Kong using the PMF ( Positive Matrix Factorization ) source apportionment method observe that at the container terminal the PM 2.5 contribution of vessels to period average mass concentration can be up to 25%. Kontos et al . 13 found that the maximum concentration of NO 2 is located near the passenger terminal and assumes the value of 270 μg/m 3 representing 135% of the hourly average limit value (LV) value (200 μg/m 3 ). Sorte et al . 14 , using the C-PORT model, assessed that the highest concentrations of PM 10 were found inside the Leixões port area. The different findings corresponding to the localization of the area of maximum impact of ship emissions are not surprising, in fact it depends on several factors: extension of the port area, the distance of the urban area, the height of funnels, wind conditions. To better characterize the effect on a local scale of the ship’s emissions in port, dispersion models can be very useful. In the present work we adopted the software CALPUFF 15 , as dispersion model. It has been often used in studies of the impact of ship emissions: (i) Poplawski et al . 4 investigated the impact of cruise ships on level concentrations of PM 2.5 , NO 2 , SO 2 in James Bay, Canada. (ii) Cruise and Passenger Ship Air Quality Impact Mitigation Actions 16 project assessed the impact on air quality and the risk to the health of the population associated with the maritime traffic of passenger and cruise. The analysis is performed for present and future scenarios with and without mitigation actions that are examined in the five port: Barcelona, Genova, Marseilles, Venice and Thessaloniki 13 , 16 (iii) Murena et al . 17 evaluated the impact of cruise ships in 2016 on the urban area of Naples. The results obtained in this study of the assessment of the impact of cruise ship emissions 17 show a significant contribution at peak concentrations episodes: the contribution to the 99 th percentile of 1-hour NO 2 concentrations can reach 86.2% during high season (June-September). The relatively low levels of pollutants, observed or simulated, in the port of Naples, may be due to the short distance of the monitoring points in port in relation to the mooring points.

As a matter of fact, the effective emission height (height of funnels plus the plume rise) for cruise ships and largest ferries may reach 60–70 meters. As a consequence, their emissions impact the ground level at a distance of about hundred meters from the releasing point. Monitoring the concentration at higher heights could be an alternative to ground level. Information on vertical profiles of pollutant concentrations in the port of Naples are not available. Only vertical average values of PM 2.5 are reported in a monitoring campaign using drones 18 . Results show how vertical average values are strongly dependent on the horizontal coordinates, namely the position inside the port area. Anyway, the port area is doubtless the best choice to locate receptor points of a monitoring network to assess and control ship emissions. In fact, this choice minimizes the need for authorization and the overlap of all the typical gas pollutants sources normally present in an urban area: traffic, heating, domestic, commercial emissions and others. However, these results show that, if you want a better characterization and the apportionment of the sources of pollution isolating the primary pollution due to port traffic activities, the best position of receptors is not always at ground level inside the port area.

Data collected in two periods of about 15 days each are reported and analysed in this paper: one (March-April 2012) characterized by low traffic and the other (November 2012) by high traffic of cruise ships.

The Case Study: the Port of Naples

The port of Naples, Fig.  1 , is embodied in the Authority of Harbour System of the Central Tyrrhenian Sea, governing body of the Campania’s port system, which includes the harbors of Naples, Salerno and Castellammare di Stabia. The port of Naples has always been a crossroads for exchanges throughout Europe. The traffic of goods and passengers affecting the port of Naples have seen a strong growth in recent years. According to the data updated to 12/31/18, the number of containers increased by 10% compared to 2017. The Neapolitan terminal is busy firstly by the traffic of passengers from ships connecting with the small islands and those with Sicily and Sardinia; great importance (and big dimension) has the passenger movement due to the cruise ships. Data updated to December 2018 show a +15.23% of cruise passengers compared to 2017 with a peak of +16.66% in the first half of 2018 (from 927.458 in 2017 to 1.068.797). The Cruise Terminal has seven piers 1,100 meters long and 11 meters of maximum depth with seven movable gangways 19 . Numerous cruises stop every year, especially in the periods of June-July and September-October when it is not impossible to have up to five ships simultaneously present in the port. Several researches have been recently developed in this port: a study assessed the acoustic impact of a Ro/Ro ( Roll on-Roll off ) pax ferry, in manoeuvre and at bollard, in surrounding areas inside the port 20 ; Murena 17 analysed the fallout of pollutants emitted by cruise ships during 2016; Langella et al . 21 analysed the effect of the changeover fuel on global emissions.

The port of Naples.

The Period Selected for Simulation

To present the methodology object of this paper, we make reference to data of monitoring collected during 2012 22 . Two periods of about 15 days were studied corresponding to two periods of the year when the presence of cruise ships was relatively low (March-April) and high (October-November). So, the first campaign has been performed in the period between March 28 th – April 10 th ; the second between the 2 nd and 14 th of November. In both cases, ships were located mostly between the wharves n.5 and 11, some in 21 and 22; the instrumented van together with instruments are represented in Fig.  2 . Data about the instruments and the results of the monitoring campaigns are detailed in 22 .

For all pollutants considered, the hourly concentration averages have been obtained in both monitoring campaigns of 2012 22 . The results are synthetically reported in Table  1 . If compared with limit values established by European directives, they cannot be exhaustive due to the limited time of monitoring campaigns. However, it can be observed that: short time averaged values (1 hr, 8 hours and 24 hours) do not never exceed the limit values established; period averages measured may be compared with year average limit values (in this case, the value of concentration of NO 2 in March-April campaign raised up to 48.4 μg/m 3 so exceeding the limit of 40 μg/m 3 ). The results obtained by campaign in 2012 showed that the mean daily concentration of NO 2 and PM 10 were always lower than the respective LVs ( Limit Values ). Period average concentrations of PM 10 and benzene were lower than the respective annual average LVs. On the contrary, period average concentration of NO 2 (41.1 μg/m 3 ) slightly exceeded the annual limit value (40 μg/m 3 ). SO 2 concentrations were much lower than the hourly and daily average LVs. Moreover, concentration levels of NO 2 and PM 10 were comparable to those recorded in the urban area of Naples in the same period.

A Simulation Study for the Optimization of Receptor Sites Inside the Port Area

The meteorological characterization of the area is fundamental for the simulation of the transport of pollutants emitted into the atmosphere. 3D wind field data have been obtained starting from the orography of the area with LANDUSE® software and WRF model (Weather Research and Forecasting) 23 . In this way, 3D hourly average values of meteorological parameters were obtained. Wind rose graphs in the monitoring days are reported in Fig.  3 . As can be seen, the prevailing direction in March-April are from SSW, while in November the prevailing direction is from NE (Nord-Est).

Rose Meteorological data: Left, March-April; right November.

The geographic coordinates of mooring points were taken from the port map of Google Satellite-based. At each ship the most frequent mooring point was assigned. For small ships (hydrofoils) the very close mooring points have been simplified in a single mooring point being negligible the effect of this different position Fig.  4 dedicated to cruise, high speed vessel and ferry.

Mooring zones (Images ©2019 Google, Images ©2019 CNES/Airbus, Maxar Technologies, Cartographic Data ©2019).

For each mooring point, distinct routes have been assumed on which we have then positioned the chimneys as sources of emissions in the phases of maneuvering and transit in port. For all the vessels present in the port, a transit phase was assumed, both in arrivals that in departures, with speeds never exceeding 3 kn. This speed has been set at a reasonable value considering the times employed by a cruise ships from the port mouths to the mooring point Fig.  5 .

Route for cruise in C3.

The manoeuver phase has been inserted always in the entry route of each ships. Therefore, we have assumed that the outbound route performed at a constant speed and almost straight. For the cruise ships the duration of the maneuver has been fixed at 20 min while for the ferries and fast vessels at 10 min. The emission of the ships in the various operational phases in port (transit, maneuvering and mooring) is one of the main input parameters of the dispersion model. A first macro-distinction shall be made between cruise ships, ferries, and fast vessels. The first step was the characterization of each type of vessels on the basis of the total power installed on board. For the maneuvering phases, a load of 20% on the auxiliary engines was assumed, and 50% on the main engine and a duration of 10 min operations (with consumption of 217 and 223 g/kWh respectively for auxiliary and main engine 24 . For these small boats, the emissions during the mooring in port have been supposed to be negligible compared to those of the cruise due to the very high demands for electric power of these ships. For the phase of transit in port, a rate of power, that the vessel will reasonably require for a propulsion with a speed of 3 kn, has been sets. Based on the simulations already carried out 17 , for the cruise ships about 13% of the total installed power was considered during the stops in port to satisfy the hoteling services. During the transit phase, the required power was calculated as the sum of the power necessary to maintain a speed of 3 kn and the power needed for the same on-board services present in the mooring phase. For the maneuver phase, instead, the engine load was divided between main and auxiliary, according to the EMEP/EEA prescription 24 : a load on the ME of 20% and on the AEs of the 50% was assumed with consumption of 223 and 217 g/kWh respectively and a total duration of 30 min. Finally, once evaluated the power in the various phases, for all ships the emission rates in g/s of NO x have been estimated by the emission factors of EMEP/EEA. Emission rate of SO x were evaluated assuming the use on board of fuels to 0.1% by mass of sulphur.

Dispersion simulations were performed by using the modeling chain composed by WRF, CALMET, CALPUFF.

The WRF model is built with a single domain. This domain is centred over the Gulf of Naples and consists of 90 columns and 90 rows of 2 × 2 km 2 grid cells. The vertical structure of the model includes 50 layers (eta levels) covering the whole troposphere. The WRF simulations were conducted with NCEP ( National Centres for Environmental Prediction ) Global Tropospheric Analyses with 1° × 1° spatial resolution and temporal resolution of 6 h.

Several physics options in WRF are available for: Planetary Boundary Layer, Surface Layer, microphysics, Land-surface and radiation. A list for each schemes using for each parameter are reported in Table  2 .

The data in WRF output files were interpreted and converted to a 3D.DAT file by CALWRF program. This file is used as the initial guess for meteorological field of CALMET.

In CALMET, we used the recommended parameters by Barclay et al . 25 with the parameters reported in Table  3 . The orography in the calculation domain was evaluated by using the software LANDUSE®. The orographic file together with a prognostic file obtained with WRF, are supplied as input to CALMET which produces the 3D weather file adjusting the meteorological field considering the local influence of high resolution data of terrain and land use.

CALPUFF is a multi-layer, multispecies, non-steady state Lagrangian Gaussian puff dispersion model that can simulate the effects of temporally and spatially variable meteorological conditions from point, line, area and volume sources. In this case meteorological fields for reference year 2016 were generated by CALMET model for a Cartesian grid, centered on the port site and subdivided into a 200 × 200 cells grid system with 50 m cell spacing. The CALMET vertical grid system considers 10 layers up to 3000 m height. To model the input of emissions in the calculation domain, 85 point sources (corresponding to ships funnel) have been defined. Eight in correspondence of mooring points. The remaining 77 point sources were placed along the arrival and departure courses to simulate emissions during maneuvering and navigation in port. Data on funnel height from sea level and diameter for each vessel category are reported in Table  4 . For ferries three different funnel’ heights were assumed depending on the gross tonnage.

The exit gas velocity was assumed at 10 m/s for all vessel categories. With all these data a file PTEMARB (Point Source Emissions File With Arbitrarily Varying Emissions) with hourly emission rates of each source point was created and given as input to CALPUFF. Chemical transformation module RIVAD/ARM3 25 was adopted to simulate chemical reactions of NO x and SO x in the atmosphere. Data for ozone required by the model RIVAD/ARM3 were obtained from the air quality monitoring network of Naples, while default values have been assumed for NH 3 , since local data are not available.

Concentrations are calculated by CALPUFF at selected points inside the port area (Fig.  6 ). To better show how the pollutants emitted by ship funnels are transported in the atmosphere, vertical profiles of SO 2 are reported in Figs.  7 and 8 . Similar results are obtained for NO 2 . The emissions include all the three phases: navigation in port, maneuvering and hoteling and all the passenger ship categories. The results show clearly that for all points selected concentrations at ground level are at a minimum with respect to those at higher height. These finding agrees with previous 22 , 26 that indicate a limited impact of ship emissions if measured at ground level inside the port area of Naples. This is a confirmation that ground level is not the best choice as receptors’ position inside the port area. It is also possible to observe that the impact increases with height. However, some differences exist among the different locations. In fact, selected points can be classified into three categories with respect to SO 2 concentration profile: moderately affected by height; highly affected by height; showing more than a maximum. At the first category belong the points where the impact of ship emissions is limited (e.g. Calata del Piliero in March-April). At the second one the points most affected by emissions from elevated funnels of cruise and ferry vessels (e.g. Stazione Marittima 1 and Stazione Marittima 2 in November); At the third one the points affected from emissions of both cruise or ferries and fast vessels (e.g. Molo San Vincenzo 3 in March-April). As can be observed the vertical profiles for the same point in the two periods may be different (e.g. Molo Immacolatella ). The main differences among all the vertical profiles are the absolute value of SO 2 concentration and the shape of the vertical profiles.

Selected points in the port area for SO 2 vertical profiles (Google IT , Data SIO, NOAA, U.S. Navy, NGA, GEBCO).

SO 2 vertical profile concentration, March-April: Up Period Average; Down 98° Percentile.

Vertical profiles of SO 2 concentration, November: Up Period Average; Down 98° Percentile.

Generally, in March-April the values of concentration are lower than November. In fact, the maximums of vertical profiles are about: 10 μg/m 3 in March-April and 128 μg/m 3 in November. For the 98° percentile at the same points the concentrations at ground level are 3.5 μg/m 3 in March-April and 2.5 μg/m 3 in November; 1 μg/m 3 in March-April and 7 μg/m 3 in November for the period average, instead the concentrations at ground level are 0.4 μg/m 3 and 6.5 μg/m 3 respectively in March-April and November. This depends on the different number of calls of cruise ships in the two periods: 19 calls in March-April (14 days) and 26 calls in November (12 days). The differences in the shape of vertical profiles depends on the rose wind pattern in the period. The results of the vertical profiles, for both periods, show that the receptor with the highest concentration level in the period March-April (Fig.  7 ) is “ Stazione Marittima 2 ”, calculated at 20 m, while in November (Fig.  8 ) the receptors with maximum concentration are: “ Stazione Marittima 1 ” and “ Stazione Marittima 2 ” in both cases at 50 m. The difference in the height of maximum concentration is probably due to the different contribution of the ship categories in consequence of the rose wind pattern in the period. In fact, the prevailing direction in March-April is from SSW (Sud-Sud West) and the receptor at the “ Stazione Marittima 2 ” is downwind respect the emission of hydrofoils (A1 in Fig.  4 ). In November, instead, the prevailing direction are from NNE (Nord-Nord Est) and NE (Nord Est) and the receptor is downwind respect to the emission of cruise ships at berth C3 and ferries anchored at berths T1 and T2 (Fig.  4 ). A confirmation of the different contribution of vessel’s categories on vertical profiles is obtained performing specific simulations for each category of vessels: cruise, ferries and fast vessels. Results are reported in Fig.  9 at the receptor point “ Stazione Marittima 1 ”. Even though, the emissions of cruise ships are much higher than those of ferries and fast vessels; their contribution at SO 2 concentration is negligible in March-April and limited in November. The highest contribution being due to fast vessels emissions. It must be highlighted that this source is the most difficult to model. In fact, mooring point and maneuvering route are often variable and the emission height is generally unknown because in many cases a real funnel does not exists.

Contribution at SO 2 airborne concentration of vessel categories at ground level (“Stazione Marittima 1”).

Our results are based upon a sample size of two periods of about 15 days. However, the shipping traffic emissions could be variable in other periods and the conclusions might be different. Considering the high cost of certified reference instruments, there is a current trend worldwide to increase the spatial and temporal data resolution and range using low-cost air pollutant sensors/monitors 27 , 28 . Utilizing low-cost air quality platforms in data collecting would be helpful in more adoptive air quality monitoring network design.

Conclusions

Data of monitoring campaigns collected in several times inside the port area of Naples showed a limited impact of ship emissions on air quality for the main pollutants: SO 2 , NO 2 , PM 10 , Benzene. This evidence is confirmed by simulations with CALPUFF for SO 2 and NO 2 emitted by passenger ships. However, this finding does not give information on the actual impact of ship emissions on the urban area of Naples. In fact, due to their height and especially of large cruise ships and ferries, plumes released by ship funnels, can impact at larger distance than that of port area boundaries. In this article, we studied the impact of passenger ship emissions, using the chain model WRF, CALMET and CALPUFF to evaluate the vertical profiles of SO 2 . Two different periods in 2012 were analyzed: 28 th March–10 th April 2 nd –14 th November. The first period is characterized by a low number of calls of cruise ships while the second by a much higher number. The results clearly show that for all selected points the concentrations at ground level are very low if compared to those at higher height. This is a confirmation of the limited impact of ship emissions inside the port area of Naples at ground level. In fact, the ratio maximum concentration/concentration at ground level ranges are between 1 and 52. In some cases, the highest concentration level is at 20 m, in other cases the maximum calculated concentration is at 50–60 m. This is mainly due to the different height of emissions of vessel categories. Fast vessels due to the small effective height of emission determine a maximum at about 20 m, while cruise ships and large ferries at about 50–60 m. Therefore, where the impact of fast vessels emissions is predominant the maximum concentration is at 20 m, where cruise or large ferries emissions prevail the maximum is at 50–60 m height. As a conclusion, results show that the ground level is not the best choice to allocate receptors within the port area because, depending on the zone, the best choice is between 20–50 m. The methodology proposed can be applied to all ports to obtain very useful information for defining the best position of receptor points of monitoring campaigns or of a monitoring network.

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The contribution of F. Murena and D. Toscano consisted of: evaluation and elaboration of meteorological data and of chemical and physical aspects; development of the dispersion model of noxious substances in the atmosphere; Figs. 3, 4, 6–9; Tables 1 and 2. The contribution of L. Mocerino and F. Quaranta consisted of: gathering data of operations of cruise ships in the port of Naples; determination of routes and power release of ships when navigating in port and moored; Figs. 1, 2 and 5; All authors contributed to introduction, conclusions and review of the manuscript.

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Mocerino, L., Murena, F., Quaranta, F. et al. A methodology for the design of an effective air quality monitoring network in port areas. Sci Rep 10 , 300 (2020). https://doi.org/10.1038/s41598-019-57244-7

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Methodological issues in studies of air pollution and reproductive health ☆

Tracey j. woodruff.

a Program on Reproductive Health and the Environment, Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California San Francisco, San Francisco, CA, USA

Jennifer D. Parker

b National Center for Health Statistics, Centers for Disease Control and Prevention, Hyattsville, MD, USA

Lyndsey A. Darrow

c Department of Environmental and Occupational Health, Emory University, Atlanta, GA, USA

Rémy Slama

d Team “Environmental Epidemiology Applied to Fecundity and Reproduction”, Inserm, U823, Grenoble, France

e University J. Fourrier Grenoble, Medical Faculty, F-38000 Grenoble, France

Michelle L. Bell

f Yale University, New Haven, CT, US

Hyunok Choi

g Harvard University, Boston, MA, USA

Svetlana Glinianaia

h Institute of Health and Society, Newcastle University, Newcastle upon Tyne, UK

Katherine J. Hoggatt

i Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA

Catherine J. Karr

j Department of Pediatrics, University of Washington, Seattle, WA, USA

Danelle T. Lobdell

k National Health and Environmental Effects Research Laboratory, US Environmental Protection Agency, USA

Michelle Wilhelm

l Department of Epidemiology, School of Public Health, University of California, Los Angeles, CA, USA

In the past decade there have been an increasing number of scientific studies describing possible effects of air pollution on perinatal health. These papers have mostly focused on commonly monitored air pollutants, primarily ozone (O 3 ), particulate matter (PM), sulfur dioxide (SO 2 ), carbon monoxide (CO), and nitrogen dioxide (NO 2 ), and various indices of perinatal health, including fetal growth, pregnancy duration, and infant mortality. While most published studies have found some marker of air pollution related to some types of perinatal outcomes, variability exists in the nature of the pollutants and outcomes associated. Synthesis of the findings has been difficult for various reasons, including differences in study design and analysis. A workshop was held in September 2007 to discuss methodological differences in the published studies as a basis for understanding differences in study findings and to identify priorities for future research, including novel approaches for existing data. Four broad topic areas were considered: confounding and effect modification, spatial and temporal exposure variations, vulnerable windows of exposure, and multiple pollutants. Here we present a synopsis of the methodological issues and challenges in each area and make recommendations for future study. Two key recommendations include: (1) parallel analyses of existing data sets using a standardized methodological approach to disentangle true differences in associations from methodological differences among studies; and (2) identification of animal studies to inform important mechanistic research gaps. This work is of critical public health importance because of widespread exposure and because perinatal outcomes are important markers of future child and adult health.

1. Introduction

In the past decade, there has been a sharp increase in the number of research articles published describing possible effects of air pollution on perinatal health, including fetal growth and preterm delivery. These papers have examined various indicators of air pollution, mostly focused on commonly monitored air pollutants (ozone (O 3 ), particulate matter (PM), sulfur dioxide (SO 2 ), carbon monoxide (CO), and nitrogen dioxide (NO 2 or oxide (NO x )) and various indices of perinatal health, including fetal growth, pregnancy duration, and infant mortality. This work is of critical public health importance because the exposure is widespread and perinatal outcomes are important markers of future child and adult health (e.g., Gillman, 2005 ). In 2004 and 2005, reviews of the preceding literature were published, generally concluding that the evidence was difficult to synthesize but was suggestive of small effects of air pollution on fetal and infant development ( Lacasana et al., 2005 ; Glinianaia et al., 2004 ; Maisonet et al., 2004 ; Sram et al., 2005 ; Tong and Colditz, 2004 ). Many recent research articles have attempted to fill in the gaps mentioned in the reviews, but the results remain difficult to synthesize.

This relatively new combination of air pollution epidemiology with perinatal epidemiology faces the challenges of both disciplines. These challenges include air pollution exposure assessment, the identification of important exposure windows during pregnancy, adequate control for potential confounding factors, and identification of effect-measure modification. One important advantage to evaluating effects of air pollution exposure during pregnancy is that time spans of exposure are relatively short, up to 9 months (assuming pre-conceptional exposures have no effect), compared to time spans from studies of chronic exposure to air pollution in children and adults, which can be years. The shorter exposure windows in pregnancy studies (typically 9 months) can make it easier to better evaluate the exposures of interest compared to longer exposures in adult studies, as it can decrease the possibility of other risk factors, both environmental and other, influencing the outcomes.

Heterogeneity in the published findings may arise from differences in many aspects of the study designs and available data. For example, studies vary in the set of pollutants considered and the methods of assigning exposure. Most studies have examined particulate matter, although the measured component varies from total suspended particulates (TSP) in earlier studies (e.g., Wang et al., 1997 ) to particulate matter with an aerodynamic diameter smaller than 10μm (PM 10 ) ( Hansen et al., 2008 ; Ritz et al., 2000 ; Sagiv et al., 2005 ) and finer particles, smaller than 2.5 μm (PM 2.5 ) in later studies (e.g., Slama et al., 2007 ; Huynh et al., 2006 ). Other pollutants examined in one or more studies include CO, O 3 , SO 2 , and NO 2 though not consistently from study to study. Further, some studies consider exposure to pollutants separately, while others consider the exposures simultaneously in an attempt to disentangle effects of specific pollutants. Multipollutant analyses have been hindered by strong between-pollutant correlations, air pollution data availability and heterogeneous degrees of spatial resolution for various pollutants. Regional and demographic differences in study populations also may contribute to the disparate findings; pollution components and mixtures can vary regionally and variation in underlying factors can contribute to population differences (such as access to care and susceptibility) and could contribute to the variations in study conclusions ( Parker and Woodruff, 2008 ).

Another challenge toward synthesis is variability in the findings by exposure windows. Of the studies that examined trimester of exposure, some found stronger effects earlier in pregnancy, others identified later exposures as more harmful and still others did not single out a particular period of pregnancy for adverse outcomes. While the method for defining the exposure windows does not vary significantly, other contributing factors, even random variation, lead to variability in findings ( Table 1 ).

Twelve studies a examining fetal growth and air pollution: number of studies examining a particular pollutant and, of these, the number of studies reporting associations between fetal growth and trimester-specific exposure, 2004–2007.

The need to better understand the unique concerns of perinatal air pollution epidemiology, to assess how methodological differences could contribute to differences in findings, and to identify important areas for future research led to two workshops in 2007, held in Munich, Germany in May ( Slama et al., 2008a ) and in Mexico City in September. The report of the Munich workshop ( Slama et al., 2008a ) covers the effects of air pollution on a wider variety of reproductive outcomes, such as fecundity and sperm quality, discusses potential biological mechanisms, methods, and recommendations for future areas of research.

The findings presented in this paper are from the Mexico City workshop. The primary goal of the Mexico City workshop was to identify differences in methodologies used among the epidemiologic studies of air pollution and perinatal outcomes as a possible explanation for the array of findings in the literature. The discussion specifically focused on studies of fetal growth and preterm birth. This paper describes the four key methodological areas focused within the workshop. These four areas were selected by the Mexico City workshop planning committee because they were thought more likely to contribute to the variation in the findings in the epidemiologic literature. Specific recommendations from the workshop to improve future studies focused on the effects of air pollution on perinatal health are then provided.

2. Objectives

The overall objectives of the workshop were to: (1) review and discuss four methodological issues that may affect findings from perinatal air pollution studies; and (2) identify priorities for future research including practical suggestions for working with existing and future data. The four methodological issues discussed were: confounding and effect-measure modification; defining exposures: spatial and temporal exposure assessment; windows of vulnerability; and multiple pollutants.

An underlying theme throughout the discussion of the four methodological areas was how to best identify the outcomes of interest, and this is briefly reviewed (for further discussion see Slama et al. (2008a) . The main findings from each of the four areas follow. We conclude this report by summarizing the key recommendations for future research to improve our understanding of the effects of air pollution on human pregnancy outcomes.

3. Identifying the outcome of interest

The majority of published air pollution and perinatal outcome studies have evaluated relationships between air pollution and different measures of fetal growth and preterm delivery ( Glinianaia et al, 2004 ; Lacasana et al, 2005 ; Maisonet et al., 2004 ; Sram et al., 2005 ). There are some studies that have evaluated other adverse pregnancy outcomes, including birth defects, spontaneous abortions or stillbirths, and infant mortality. The Mexico City workshop discussion primarily focused on air pollution effects on fetal growth and preterm delivery, consistent with the majority of the scientific studies. Studies have evaluated a number of different metrics to describe potential effects on fetal growth, including reduction in birthweight (continuous variable), low birthweight (defined as <2500g), very low birthweight (<1500g), and intrauterine growth retardation (often measured as low birthweight in full-term infants or small for gestational age, which has been defined as birthweight below the 10th percentile of the birthweight distribution for a specific gestational age and sex based on national standards for livebirths) ( Glinianaia et al., 2004 ). Most of the studies acknowledge the potentially different etiology of growth restriction (as compared to preterm birth) by assessing birthweight at term, and/or accounting for gestational age in the models. A number of studies have also evaluated preterm delivery, which is most often measured across the studies as birth at less than 37 completed weeks of gestation. Although the dating of gestational age can vary by study, many studies use the woman’s recall of date of last menstrual period (LMP).

While participants noted difficulties in identifying appropriate pregnancy endpoints, these problems are not unique to studies of air pollution. Birthweight, for example, is a sensitive but not very specific endpoint for studies of exposure. Birthweight distributions for healthy infants can differ by subgroups characterized by a variety of factors (e.g., race or gender); and the consequences of low birthweight (and other fetal growth outcomes) can also differ among factors, including different exposures, hypothesized to be responsible for inadequate growth. Another problem common to perinatal epidemiology that affects studies of air pollution is distinguishing between reduced birthweight resulted from fetal growth restriction or from preterm delivery, or both. A recent study has used ultrasound images during mid-gestation to evaluate the relationship between fetal growth and air pollution ( Hansen et al., 2008 ), which is one approach to distinguishing fetal growth effects from preterm delivery effects. Hansen et al. (2008) study accounted for gestational age in the model using a validated measure of last menstrual period which was not based on ultrasound data. Accounting for gestational age when using single ultrasound measurements in these types of studies is important because ultrasound is also used to establish gestational age, and smaller infants may be mistaken for younger gestational age, rather than as growth retarded ( Slama et al., 2008b ).

4. Confounding, effect-measure modification, and selection bias

The role of air pollution in perinatal outcomes and the potential for confounding can be considered by the following question: “Is the association of air pollution and birth outcome confounded by personal characteristics or is air pollution one explanation for the association of personal characteristics with birth outcome?” The intersection of air pollution epidemiology and perinatal epidemiology is not particularly straightforward. Air pollution epidemiology, on the one hand, has often relied on time-series analyses relating daily pollution levels to daily counts of health events, usually with a lag of a few days; in this setting there is concern for weather-related confounders such as temperature and less concern about confounding from personal characteristics constant over time which are controlled for by the study design. On the other hand, perinatal studies often use binomial regression models (e.g., logistic) to obtain risk ratios or odds ratios and often compare populations from different geographic areas. In this type of study, in addition to confounding due to seasonally varying factors, concerns arise about potential confounding by maternal characteristics such as age, race/ethnicity, body mass index, socioeconomic status, and behaviors, particularly smoking, which are usually not controlled by study design. The availability, quality, and impact of these potentially confounding factors can vary by study, though most published studies used covariate data collected from birth certificates.

Much of the research on air pollution and birth outcomes is based on data sets formed by combining individual information from birth records with measures of ambient air quality, typically from outdoor stationary monitors. While the birth records typically contain information related to birth outcomes, such as maternal age, educational attainment, and parity, there is concern that unmeasured individual-level characteristics, not available on the birth record, may confound observed relationships. Confounders were primarily considered as covariates that may distort the association between the pregnancy outcome and the air pollution exposure; more detailed definitions of confounding, excluding factors that are potential consequences of either exposure or outcome, can be found (e.g., Rothman et al., 2008 ; Jewell, 2004 ; Selvin, 1991 ). Social class indicators are thought to be important confounders, for example, because lower socioeconomic status women are at increased risk of poor birth outcomes and, at least in some countries, are more likely to live in polluted areas. Importantly, some covariates may have a different relationship in an analysis. If air pollution affects a birth outcome through its effect on one or more covariates, these covariates are not considered confounders. In studies of air pollution and perinatal outcomes, potential confounders which may be either poorly measured or absent in analyses include socioeconomic status indicators beyond those collected on the birth certificate, such as family income and behavioral variables, such as substance use. Confounding was discussed separately from effect-measure modification, which for specific statistical models could allow identification of subgroups more vulnerable to effects of air pollution. For example, there is speculation that associations may be stronger for male than female infants ( Ghosh et al., 2007 ), and could be stronger for mothers in poorer neighborhoods compared to those in wealthier neighborhoods ( Ponce et al., 2005 ), though another study suggests associations could be stronger for women in wealthier neighborhoods ( Genereux et al., 2008 ). The same variables can be confounder or effect modifiers depending on the characteristics of the study population, or the underlying hypothesis. Associations between socioeconomic status and pollution exposure may vary geographically or according to the spatial resolution of the exposure model and could contribute to differing relationships with birth outcomes.

Recent results from a nested two-phase study provide insights into the potential influence of confounding ( Ritz et al., 2007 ). Information from birth records was augmented with information from a detailed interview survey for a subset of the overall study population to examine whether factors not included on the birth certificate affected the air pollution - preterm delivery relationship. The authors reported that many initially hypothesized confounders, such as smoking or body mass index (BMI), did not have a large effect on the air pollution/preterm delivery relationship in their cohort and that existing variables on the birth certificate were apparently sufficient to control for potential confounding by these factors. However, they did note that other factors being more closely examined in future studies (time activity patterns) may have a larger impact on the effect estimates, either as confounders or as inputs into more precise exposure measures. A study from Germany reported that the covariates of maternal height, education, and gestational age had the largest effects on the estimated relationship between air pollution and birthweight based on comparison of adjusted and unadjusted models ( Slama et al., 2007 ). A study of the potential confounding effects of smoking found that while maternal smoking was a risk factor for respiratory-related infant mortality, it did not confound the PM and infant mortality relationship ( Darrow et al., 2006 ).

Confounding from unmeasured factors could depend upon the (spatial or temporal) resolution of the exposure model. For example, in a study in Connecticut/Massachusetts, air pollution was averaged at the county-level ( Bell et al., 2007 ), corresponding to a comparison of different exposures within a county (e.g., different timeframes of births) as well as to a between-county comparison and thus estimated air pollution associations could be confounded by factors that also vary within the county (for example, certain personal characteristics). However, the relationship between PM and birthweight was similar to a study in Los Angeles using a smaller geographic area (zip code) ( Wilhelm and Ritz, 2005 ). Effect-measure modification may be more difficult to identify over broad geographic areas which could also influence observed results (e.g., effect modification by race) though in some studies with relatively large spatial exposure scales still find effect modification by race ( Bell et al., 2007 ). Some of these factors which differ among women, such as race and education, can be controlled for within an analysis, but other unconsidered factors, such as place-specific factors (e.g., neighborhood related) or individual factors (e.g., income), could still have an effect, either as confounders or effect modifiers.

An issue related to the scope of geographic coverage used in the studies is the potential for selection bias when mothers are excluded from the study because they are not living near monitoring locations. Studies vary in how exposure metrics are constructed from air monitoring data, with some using administrative units such as county or postal codes areas, and others constructing exposures directly for maternal residences. In either case, mothers living near monitors may differ from those living far from monitors ( Basu et al., 2004 ; Slama et al., 2007 ; Parker and Woodruff, 2008 ). Agreement on whether geographic scope of constructed metrics of air pollution exposure contributed to selection bias was not reached; some workshop participants thought the inclusion of mothers living near monitors affected generalizability rather than bias.

It was also noted that it is important to consider the larger geopolitical context. The studies to date have primarily been done in industrialized countries, such as Australia, Canada, the US and Europe, where the sources and levels of pollutants are much different from non-industrialized countries. The impact of air pollution is likely to be much larger in non-industrialized countries, which have poorer air quality and more vulnerable populations. However, understanding the impacts of pollution on perinatal health in non-industrialized countries may be particularly complicated as confounding factors (diet, socioeconomic measures, co-morbidities, etc.) and contributions from other air pollutant sources, such as coal and indoor fuel use, probably have wider within-population variation than in the developed countries.

4.1. Next steps

One possible tool to clarify the role of intrinsic and extrinsic risk factors on the exposure-outcome relationship is to create a conceptual framework for distinguishing confounding variables from those on the causal path; for example, if air pollution is related to birthweight, in part, via a measured maternal outcome, such as pregnancy-induced hypertension, then controlling for hypertension (or excluding those records) in an analysis may lead to biased inferences. Essentially, there is difficulty in distinguishing between the possible direct effects of air pollution on fetal growth and the possible effects of air pollution on other pregnancy factors, which in turn can be independent risk factors of fetal growth restriction and/or make pregnancies more susceptible to air pollution. Pregnancies which are predisposed to poor pregnancy outcomes may form susceptible subgroups with increased vulnerability to air pollution or may have poor outcomes independently of air pollution. In other words, assessing air pollution effects among a potentially susceptible subgroup defined by a specific condition predisposed to adverse birth outcome requires care to disentangle any air pollution effects from effects of other factors related to the condition (e.g., severity of a condition, amount of exposure to other agents). To date, few studies have evaluated potential intermediate outcomes.

As in other epidemiological studies, even within a hypothesized conceptual framework it is difficult to assess the extent of residual confounding that may remain after control for available covariates, so the plausibility of the phenomenon being investigated is critical. Plausibility of residual confounding by poorly measured or unavailable covariates should also be considered by investigators in the context of each study location and design. Some assessment of plausibility must come through the investigator’s experience and the weight of scientific evidence, although quantitative assessment of the underlying assumptions using sensitivity analyses is also critical. Clinical and/or animal studies would provide useful information on intrinsic and extrinsic risk factors that may influence air pollution and perinatal outcomes.

While the role of effect-measure modification in studies of air pollution and birth outcomes was not discussed thoroughly, it was mentioned that large data sets may be needed to sufficiently identify all subgroups of interest and assess effect-measure modification, though given a strong enough effect, smaller numbers could be used to identify differences. These data sets, if obtained from broad geographic areas, have an added advantage of wider exposure variation for analysis. However, large data sets tend to have fewer variables available for confounder control, and wider geographic coverage can increase the heterogeneity of the sample and thus increase the risk of residual confounding.

The following specific recommendations were suggested to further address potential issues of confounding:

• Consider time-series or temporal studies, as appropriate, which are less vulnerable to confounding by personal characteristics not varying in time.
• Compare characteristics and results for mothers residing at varying distances from air monitors to investigate the possible effects of choosing different study samples on results (e.g., Basu et al., 2004 ; Slama et al., 2007 ; Parker and Woodruff, 2008 ).
• Use a two-phase design and augment the large data sets with additional covariate information from a survey for a subset of the births. This detailed covariate data can be used to further assess potential confounding factors on the estimated relationships within the context of the larger data set.
• Identify natural experiments where locations experienced large changes in air pollution levels to assess changes in birth outcomes.
• Use matched birth records of siblings where underlying maternal characteristics may be similar but exposures may differ for subjects.
• Explore implications of less-commonly considered potential confounding factors such as house size, where a larger house is an indicator of wealth but could also affect air pollution exposure through various mechanisms, such as differing construction quality or air volume.
• Consider area-level indicators of potential confounders, such as area level median income or housing characteristics.

5. Defining exposures: spatial and temporal exposure assessment

Because pollution monitors are not sited everywhere people live and do not always provide continuously measured data (i.e., PM 2 .5 in the US is often measured every 3–6 days, whereas other pollutants such as CO are measured hourly), there is a growing literature on the use of spatial and temporal models to predict air pollution exposure for places and times without monitoring data. Although the combination of both the spatial and temporal components of exposure variability has increased the statistical challenges for exposure estimation, for studies of air pollution and pregnancy outcome, spatial and temporal exposure models could improve exposure assignments. This could be accomplished by considering both the mother’s residential locations and the timing of relevant periods of pregnancy in the predictions. Banerjee et al. (2003) and Diggle and Riberiro (2007) provide statistical overviews of these models; Slama et al. (2007) and Brauer et al. (2008) provide examples of land-use regression model-based exposure estimates in perinatal studies.

The Particulate Matter and Perinatal Events Research (PAMPER) study provides an example of how to consider spatial and temporal exposure surfaces for a health study ( Fanshawe et al., 2008 ). The study was designed to examine associations between maternal exposure to black smoke and birth outcomes in Newcastle upon Tyne, England over a 32-year period starting in 1961. Since few monitoring data were available for black smoke, an important aspect of determining exposures was model black smoke predictions and their associated variances so that both could be used when assessing the strengths of the associations between black smoke and birth outcomes. In the case of the PAMPER study, temporal variation was more important than spatial variation for exposure predictions because of the long study period with a dramatic decline in black smoke levels. Strong seasonal patterns of the exposure over time also necessitated the development of flexible prediction models that allowed for locations and magnitudes of seasonal trends to vary annually. Additionally, “constructed covariates”, surrogate measures of pollution sources that correlate well with exposure when there is insufficient exposure data, were found to be a practical way to reduce residual spatial-temporal correlations and allowed for less complicated model structures. As an example, chimney density was found to be a good predictor of black smoke in the PAMPER study. Surrogate measures may be appropriately used either to improve spatial-temporal models or as exposure indicators in epidemiological analyses. Using validated indicators on their own in an analysis is important, as air pollution data may not be available in all locations of interest. Other recently used exposure surrogates include traffic-use patterns, distance to roadways, and land-use patterns ( Slama et al., 2007 ; Wilhelm and Ritz, 2005 ).

Another aspect to assessing exposures is the role of season in analytic models, especially if spatial/temporal prediction models are fitted seasonally. Season can represent many things, including variations in temperature and other weather patterns, allergy susceptibility, food availability, and environmental exposures (pesticides, water quality), any of which may contribute to observed geographic differences in associations between season and birth outcomes (e.g., Chodick et al., 2007 ; Matsuda et al., 1995 ; McGrath et al., 2005 ; ] Rayco-Solon et al., 2005 ). Some seasonal factors that differ geographically - such as nutritional status - vary throughout the year in many locations but probably have greater impacts in non-industrialized than in industrialized countries. Other factors, such as temperature, can also differ geographically, but with different patterns (e.g., California versus Northern New England). In addition, just controlling for season may not fully account for the effects of some seasonally-varying factors. Temperature, for example, which varies with season, may need to be specifically accounted for in an analysis as variations in temperature within a season may be important, though temperature has not been thoroughly evaluated as a potential risk factor. Consequently, importance of season-related variables in air pollution studies likely differs by birth outcome and location under investigation.

5.1. Next steps

5.1.1. spatial scale.

The importance of temporal and geostatistical modeling for exposure assessment depends on the study’s context, such as length of study period and the magnitude of the spatial and temporal variation of the pollutant being studied. In some cases, area-level average air pollution data may be sufficient enough to represent individual-level exposures, such as chronic exposure to pollutants that are evenly dispersed over relatively large geographic areas (e.g., coarse PM), for example, using average air pollution concentrations within a political unit, such as county. In other cases, modeling exposures at a finer scale will be more important. Different methods of exposure assignment capture different aspects of pollution. Some pollutants are spatially heterogeneous on a smaller scale and may be very sensitive to exposure definitions (e.g., CO, ultrafine particles), whereas others are more homogenous and can be represented by larger spatial averages (e.g., PM 2.5 ). Furthermore, some underlying pollution sources vary more locally, others more regionally (e.g., traffic as a contributor to area-level averages, wood smoke, industrial sources). It was hypothesized that smaller scale studies may be better for understanding biological mechanisms and contribute more information for local policies while larger scale studies may be better for looking at population-level factors and may be better for regional policy. However, the relative importance of small and/or large scale geographic areas in the study of air pollution and perinatal outcomes has not been systematically examined.

5.1.2. Surrogates

Surrogate measures of pollution may be important in the development of spatial and temporal prediction models, especially surrogates that incorporate seasonal trends and are relatively inexpensive to obtain. Monitoring network locations are sited for policy and regulatory purposes, not for health studies. Consequently, they are useful, but not ideal, for epidemiological investigations, and additional monitoring in targeted locations may not be possible for all studies. Several surrogates were mentioned or suggested, such as the chimneys in the PAMPER study, traffic patterns, and other characteristics used in land-use regression models. Satellite maps have potential for providing surrogate information for air pollution levels but can be limited due to various factors, such as weather (e.g., no measurements during cloudy days) and weekly reporting patterns. Surrogate measures of pollution obtained from non-conventional sources could also be used directly in epidemiological studies as alternatives to monitoring data or as inputs into prediction models; an initial list of proposed surrogate devices include contact lenses (which capture particle pollution), sleep apnea monitors (which have a filter that could be analyzed for air pollution), and house plants (which capture certain types of air pollution such as metals).

The potential influence of residual spatial and temporal correlation in analytic models was also considered. Workshop participants who had examined this issue did not report serious autocorrelation problems in their analyses; however, no comprehensive evaluations were mentioned and may be warranted. As mentioned above, the use of strong surrogates can reduce the need for more complicated models of spatial and temporal correlation.

5.1.3. Season

Further evaluation of the role of season and whether it is independently associated with birth outcomes, whether it is a surrogate for other factors that are associated with birth outcomes (e.g., temperature, food availability, etc.), whether it is a proxy for pollution exposure, or whether it may not be a confounder at all in certain locations was identified as an important area of further research.

The following specific recommendations were suggested to further address issues related to spatial and temporal exposures:

• Systematically assess the relative contributions of using small and large geographic scales to assess air pollutant exposures and any subsequent influence on effect estimates.
• Further evaluate and validate exposure surrogates or alternative exposure metrics.
• Evaluate the potential influence of spatial and temporal autocorrelation.
• Evaluate the most appropriate way to address season in different types of studies—this includes a better understanding of the implications of season as a variable in perinatal studies given the seasonal trends in births, air pollution exposures, and many other factors; both statistical approaches and seasonal indicators need to be explicitly examined.

6. Exposure windows

The third area of methodological challenge is identifying whether there are particular periods of susceptibility during pregnancy when air pollution exposure is particularly harmful to fetal health and development. Early pregnancy could be one time of enhanced susceptibility, as this is when placental attachment and development occurs, or susceptibility may increase toward the end of pregnancy when the fetal growth velocity is highest. Evaluating periods of susceptibility can provide insight into potential biological mechanisms and allow for defining more accurate measures of effect as the exposure estimate of interest can be more precisely defined. Most published studies have primarily focused on evaluating exposure by trimester, though a few have also assessed exposure by gestational month. The literature on air pollution and preterm delivery or growth restriction to date, has not identified a specific time window of susceptibility. In studies of fetal growth, some studies have reported effects due to first trimester exposures, while others report effects only for third trimester exposures ( Table 1 ). Fewer studies report effects from second trimester exposure, and some report effects for more than one trimester of exposure. Findings are similar for preterm delivery. Some of the apparent differences by trimester may be due to the varied methods used to consider (or not consider) correlated exposures among trimesters or pollutants.

Identification of a particular window of susceptibility is difficult. If air pollution is associated with growth restriction or preterm delivery, yet there is no particular critical window, then the trimester (window) of exposure that will appear to be important is that which is most highly correlated with whole-pregnancy exposure. In addition, it is difficult to distinguish one trimester from other time periods as being important because exposures among the trimesters are correlated. In studies of preterm delivery, additional care is needed to define windows of exposure given the shorter length of pregnancy for the preterm compared to the term births (e.g., Huynh et al., 2006 ; O’Neill et al., 2003 ).

There are several new ideas that could provide insight into this issue. A recently applied method used by Bell et al. (2007) was highlighted as a potentially useful approach to simultaneously adjust for all trimester-specific exposure variables. In this study, exposure during each trimester was modeled as a function of exposure in the other trimesters, and the residuals from these trimester specific models were included in the subsequent trimester-specific regression models to control for other trimesters’ exposure. The use of post-pregnancy exposure as a control category to examine the robustness of the whole or partial-pregnancy exposure has also been suggested ( Slama et al., 2007 ); specifically, if whole-pregnancy exposure is an etiologically relevant window, then the pregnancy exposure variable should be more consistently associated with pregnancy outcome than the post-pregnancy exposure. A limitation to this approach is that observed associations between post-pregnancy exposure and pregnancy outcome may be due to a high correlation between post-pregnancy and within-pregnancy air pollution exposures.

6.1. Next steps

Trimesters have been used to define pregnancy periods for decades, but do not completely correspond to critical windows of fetal developmental. Periods of susceptibility depend on the outcome being evaluated; for example, potentially relevant exposure periods for congenital anomalies, in particular, differ from those for fetal growth or preterm delivery. Thus, using trimesters to define exposure windows could inaccurately define periods of susceptibility.

It was recommended that exposure windows shorter than trimesters (mostly gestational months) should be evaluated in epidemiological studies to try and capture more relevant fetal development periods. However, it was recognized that trimester-level results offer some comparability with existing studies, as this is the most common exposure window used, easing research synthesis. If shorter time exposure windows are used, it is important to consider that the accuracy of exposure metrics may differ by the size of the exposure windows. For example, shorter windows, such as a month, may entail larger exposure misclassification when frequent measurements are not available (i.e., in areas where PM is monitored every 6 days) compared to longer windows, such as the entire gestation. In addition, the question was posed whether it matters if the fetus is exposed early and late in pregnancy or just early or just late. The evaluation of different patterns of exposure throughout pregnancy was identified as important. Particularly in studies using short time frames, such as weeks, the non-linear pattern of fetal growth and development should be considered, although a particular method for accomplishing this was not defined. A large number of windows to be examined can lead to a multiple comparisons problem; to minimize the occurrence of random findings, one suggestion was to identify potential windows of importance a priori through animal experiments. Considering shorter and longer windows of exposure will inform considerations of the importance of acute and chronic exposures.

Defining more narrow windows of susceptibility requires some confidence in the gestational age, which is typically taken from the birth certificate, and in some locations, may be less precise than birthweight because it is based on recall of last menstrual period (e.g., many areas in the US). One possible approach to more precisely measure gestational age is to use data from fertility clinic-based studies, where exact dates of conception are known, and pre-conception exposures can be studied, including paternal exposures. However, it was noted that the high correspondence between paternal and maternal (non-occupational) exposures makes separating parental effects difficult when personal exposure estimates are not available. One drawback to fertility clinic records is that pregnancies resulting from assisted conception are at higher risk of adverse birth outcomes than naturally conceived pregnancies, which would reduce the generalizability of the results ( Reddy et al., 2007 ). Nevertheless, while fertility clinic populations may be unique, their detailed data may offer important insights into gestational age issues related to windows of exposure.

Although human fetal development differs from other species, animal studies might be informative in understanding vulnerable windows; the current toxicological and biological knowledge for air pollution impacts on human health is limited and is particularly limited for reproductive outcomes. Animal studies may be particularly useful for studying effects of high exposures during specific pregnancy periods.

The following specific recommendations were suggested to evaluate potential periods of susceptibility:

• Exploring other potential periods of susceptibility besides trimesters, in particular shorter ones, such as gestational months (keeping in mind for pollutants not monitored daily, the fewer available monitored values). Further, examining exposure over time as a continuous rather than categorical metric, and considering peaks of exposure, may increase our understanding of windows of vulnerability.
• Applying comparative analyses across different study populations with efforts toward similar methods and definitions of both windows of exposure and outcomes represents a promising approach to resolve some of the inconsistencies observed in the literature.
• Identifying relevant gestational windows of susceptibility by outcome. This identification will likely be informed by general perinatal (e.g., risk factors other than environmental contaminants) and toxicological studies.

7. Multiple pollutants

A fourth issue in evaluating the existing air pollution and perinatal outcomes literature is the variability in the types of air pollutants evaluated and which individual pollutants or combination of pollutants are identified as the pollutant(s) associated with the perinatal outcome. Existing studies in the US primarily assessed exposures to “criteria” air pollutants (particulate matter, ozone, carbon monoxide, sulfur dioxide, nitrogen dioxide), with most studies evaluating exposure to particulate matter (both PM 2 .5 and PMi 0 ), ozone, carbon monoxide, nitrogen dioxide, and to a lesser extent sulfur dioxide ( Table 1 ). Assessing which pollutants, if any, are risk factors for poor birth outcomes is complicated by using ambient air monitors for exposure assessment. Ambient air monitoring introduces measurement error into the exposure estimates. In addition, the monitoring schedule for the pollutants varies, as some pollutants such as ozone are reported every hour, and others, such as PM, maybe reported once every six days, which can affect how well the monitoring data represent exposures over shorter periods of times (e.g., weeks).

The workshop focused on two fundamental issues in exposure assessment of multiple pollutants, measurement error and surrogate exposures using four scenarios as examples ( Table 2 ). In general, model results may be very sensitive to measurement error (the difference between measured ambient levels and personal exposure to ambient pollution) and correlations between the pollutants. However, because pollutants are often from common sources it is difficult to separate the etiological agents, the surrogates, and confounders ( Tolbert et al., 2007 ; Sarnat et al., 2001 ; Kim et al., 2007 ). Using a priori knowledge about the measurement error of the pollutants and their interrelations can help guide interpretation of models for multi-pollutant exposures. Identifying the sources of the pollution and assessing pollution mixtures offer complementary strategies to the more common approach of evaluating specific pollutants individually and may be particularly important if source or the mixture is the important risk factor.

Different interpretations of the same multi-pollutant regression model under four different scenarios of two correlated pollutants, pollutant1(P1) and pollutant(P2).

7.1. Next steps

There has been variability in which pollutants have been considered in perinatal studies and how they are considered (individually or simultaneously). An effort to systematically evaluate the contribution of different pollutants across multiple studies using the same methods for specifying exposure metrics could be helpful in evaluating the robustness of findings across different studies.

It was noted that focusing on individual pollutants as the single risk factor is likely not to reflect the effect of combined exposure to multiple air pollutants, and it could be the mixture represents a higher risk than the individual components, similar to tobacco smoke. The primary source of many pollutants is combustion, and one potentially fruitful area of inquiry is to consider the source of the pollutants as the metric for exposure, rather than the individual constituents. The case of tobacco smoke, which is similar to traffic-related air pollution in that it is a mixture of constituents from a combustion source, provides an example of evaluating exposure on a source basis. An additional advantage of a source-based approach is that it is not necessary to identify the individual etiologic components for public health interventions. In the case of combustion, it is a little more nuanced, as there are multiple environmental combustion sources of pollution (e.g., motor vehicle versus wood burning), and knowing the specific components of exhaust responsible for health effects could help regulation and technologies for harm reduction.

To consider combustion sources, a next step is to identify measures of combustion and describe how they differ by source. It was suggested that CO might be a good surrogate for motor vehicle exhaust. The similarity of associations in perinatal studies in Los Angeles over a fairly long time span when CO levels were dropping suggests that some other agent in motor vehicle exhaust that is correlated with CO may be the etiological agent ( Ritz and Yu, 1999 ; Wilhelm and Ritz, 2005 ; Ritz and Wilhelm, 2008 ). However, CO is a spatially heterogeneous pollutant, and measured levels at monitoring stations may only reflect concentrations within a small distance of the monitor. Future efforts to identify which pollutants are good surrogates of exposure and using a source-based approach are important areas for future research.

It was noted that there could be a synergistic response from exposure to multiple pollutants. Understanding this effect would require different study designs or analytical strategies than those that have been used to date. It was suggested that creating informal graphical models of different multiple pollutant scenarios, including supplemental information on the specific pollutants, would help direct future studies ( Woodruff et al., 2003 ). These models would be more consistent with an interval estimation framework (e.g., credible intervals in a Bayesian context as discussed in Dunson, 2001 ; Gelman and Hill, 2007 ) than significance testing or p-values. Small validation studies of pregnant women (e.g., assessing personal-ambient exposure correlations) would help researchers disentangle the influences of multiple pollutants and identify which pollutants act as etiologic agents, confounders, and/or surrogates.

As noted above, there is a tendency for multiple pollutant studies to focus on regulated, and routinely monitored, common air pollutants, even though these pollutants may not be the only pollutants of etiologic interest. In the United States, measurements of PM, O 3 , NO 2 , SO 2 and CO are readily available for many urban areas, although every pollutant is not monitored in all locations. Other air pollutants, such as those listed as hazardous air pollutants under the Clean Air Act, should also be examined. For these pollutants, there is less wide-spread monitoring data readily available. The increasing use of modeled exposure data may promote studies of other air pollution indices, and these data are available for several years for the hazardous air pollutants in the United States (information available at http://www.epa.gov/ttn/atw/natal999/ ).

Workshop participants further recommended:

• Incorporate indicators of exposure precision into statistical models explicitly rather than speculating on effects of measurement error; this is important for both model-based estimates and also for the exposure estimates based on temporal and spatial averaging of ambient air monitoring data ( Van Roosbroeck et al., 2008 ).
• Evaluate the effect of residential and occupational mobility during pregnancy, which can affect exposure estimates based on maternal address at birth.

8. Summary and conclusion

The research of air pollution and perinatal outcomes is a rich and growing field. The evidence to date suggests that air pollution may play some role in adverse pregnancy outcomes, and the importance of pregnancy outcomes in future health of the child make air pollution an important area of further inquiry and intervention. Perinatal outcomes have only been recently considered in policy and regulatory activities related to air pollution, and their contribution as a source of preventable disease could be substantial internationally. In this paper, we explored four areas of methodological interest that the workshop planning committee identified as varying among the published studies to date and/or were thought more likely to contribute to the variation in the findings in the epidemiologic literature. We provided recommendations specific to these areas to move this field forward and extend the discussions and recommendations from a previous workshop on the broader topic of air pollution and reproductive outcomes ( Slama et al., 2008a ).

To leverage the existing literature to date, participants noted the importance of collaboration among researchers in different countries worldwide who have been investigating this phenomenon. In addition to the topic-specific suggestions above, participants made several general recommendations for future research priorities to better elucidate the role of air pollution and perinatal outcomes.

• A key next step would be to develop an international collaborative among researchers in the field to apply the same or similar methods to analyzing the existing data sets. Some of the methodological differences identified at the workshop included gestational exposure windows, the set of adjustment variables (including co-pollutants), use of seasonal variation, and spatial resolution. Applying a consistent analytic strategy across many data sets may help to reconcile some of the apparent inconsistencies in effect estimates observed across studies. Furthermore, this type of research synthesis would help in guiding policy.
• Participants noted that it is critical to identify animal and cell studies to inform each of the areas discussed above. In particular, animal studies can be used to inform gestational windows of susceptibility to air pollution, reproductive endpoints that are difficult to ascertain with available epidemiological data (e.g., miscarriage, placental development), and specific pollutants or pollutant mixtures of etiologic interest. These studies can also be used to evaluate more precise measures of exposure in a homogenous population. Collaborating more closely with toxicologists to develop a priority list of experiments was noted as an important next step.
• Expanding the types of outcomes considered in studies, including fetal loss (both as a pregnancy outcome and as a potential bias in studies of live births) and pregnancy related hypertension or preeclampsia, may provide insights into both mechanisms and other susceptible outcomes.

Acknowledgments

The findings and conclusions in this paper are those of the authors and do not necessarily represent the views of the US Centers for Disease Control and Prevention or the US Environmental Protection Agency. To focus the report, an effort was made to represent the conversation during the workshop. However, particular points raised and noted here may not be universally agreed upon by all participants; time constraints did not allow for all counter points to be made during the workshop.

This represents the findings from the Workshop on “Methodological Issues In Studies Of Air Pollution And Perinatal Outcomes”. We would like to acknowledge the following: the workshop organizers were Jennifer D. Parker and Tracey J. Woodruff; the session moderators were Kathleen Belanger, Peter Diggle, Remy Slama, and Lyndsey A. Darrow; the session note takers were Matthew Strickland, Rakesh Ghosh, Jo Kay Ghosh, Hyunok Choi; the workshop participants were Kate Adams, Kathleen Belanger*, Michelle Bell*, Michael Brauer, Hyunok Choi*, Aaron Cohen, Adolfo Correa, Lyndsey Darrow*, Peter Diggle, Svetlana Glinianaia*, Ulrike Gehring, Jo Kay Ghosh, Rakesh Ghosh, Nelson Gouveia, Irva Hertz-Picciotto, Katherine J. Hoggatt*, Catherine Karr*, Nino Kuenzli, Danelle Lobdell*, Rachel Morello-Frosch, Marie O’Neill, Jennifer Parker*, Frank Pierik, Beate Ritz*, Paulo Saldiva, Remy Slama*, Matthew Strickland, Ondine Von Ehrenstein, Daniel Wartenberg, Michelle Wilhelm*, Tracey Woodruff*.

*Workshop planning group. Tanja Pless-Mulloli and Judith Rankin were on the planning group but were unable to attend the workshop.

This represents the findings from the Workshop on “Methodological Issues in Studies of Air Pollution and Perinatal Outcomes”. Funding for the workshop was provided by: Association of Occupational and Environmental Medicine Clinics, University of Washington, Seattle; Center for Occupational and Environmental Health and Fogarty Center, University of California at Los Angeles; Health Effects Institute; Institute of Health and Society, Newcastle University; Program on Reproductive Health and the Environment, National Center of Excellence in Women’s Health, Department of Obstetrics, Gynecology, and Reproductive Sciences, University of California at San Francisco; School of Forestry and Environmental Studies, Yale University.

☆ Disclaimer: This paper has been subjected to review by the National Health and Environmental Effects Research Laboratory and the Centers for Disease Control and Prevention and approved for publication. The findings and conclusions are those of the authors. Approval does not signify that the contents reflect the views of the USEPA or CDC, nor does mention of trade names or commercial products constitute endorsement or recommendation for use.

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Managing Air Quality - Control Strategies to Achieve Air Pollution Reduction

A control strategy related to air quality is a set of specific techniques and measures identified and implemented to achieve reductions in air pollution to attain an air quality standard or goal.

On this page:

Considerations in Designing an Effective Air Quality Control Strategy

Controlling sources of pollution.

• Need for Controls Applied Regionally or Nationally in Addition to Locally

What are the Steps in Developing a Control Strategy?

• Environmental: factors such as ambient air quality conditions, relevant meteorological conditions, location of the emissions source, noise levels, and any ancillary pollution from the control system itself.
• Engineering: factors such as pollutant characteristics (such as abrasiveness, reactivity and toxicity), gas stream characteristics, performance characteristics of the control system, and adequate utilities (for example, water for wet scrubbers).
• Economic: factors such as capital cost, operating costs, equipment maintenance, equipment lifetime, and administrative, legal, and enforcement costs.
• The U.S. Environmental Solutions Toolkit  is a user-friendly database that highlights scientific analysis, regulatory structures, and some examples of U.S. companies offering relevant solutions.
• Learn more about Export Promotion at EPA .

Pollution prevention approaches  to reduce, eliminate, or prevent pollution at its source, should be considered. Examples are to use less toxic raw materials or fuels, use a less-polluting industrial process, and to improve the efficiency of the process.  

The Clean Air Technology Center serves as a resource on air pollution prevention and control technologies, including their use, effectiveness and cost. Examples are mechanical collectors, wet scrubbers, fabric filters (baghouses), electrostatic precipitators, combustion systems (thermal oxidizers), condensers, absorbers, adsorbers, and biological degradation.

Controlling emissions related to transportation can include emission controls on vehicles as well as use of cleaner fuels.

Economic incentives , such as emissions trading, banking, and emissions caps can be used. These strategies may be combined with the "command-and-control" type regulations which have traditionally been used by air pollution control agencies.

Need for Controls Applied Regionally or Nationally in Addition to Locally

Air pollution does not recognize geographic boundaries.  Some pollutants can travel great distances affecting air quality and public health locally, regionally, nationally, and even internationally in areas that are downwind.

For this reason, control strategies to improve air quality in local areas need to include control measures that are mandated and implemented on a state, region-wide or national basis. In general, regulations established by the national government tend to have the widest application, which can minimize boundary and economic competition issues.

In the United States, the Clean Air Act requires that each state’s implementation plan contain provisions to prevent the emissions from the facilities or sources within its borders from contributing significantly to air quality problems in a downwind state. Learn more about the approach in the United States to address interstate air pollution transport .

• Determine priority pollutants. The pollutants of concern for a specific location will be based on the nature of the associated health or environmental effects and the severity of the air quality problem in that area.                                                                                                                                                                                                   
• Identify measures to control sources of pollution.                                                                                                                                                                                                                          
• Develop a control strategy and plan that incorporates the control measures. The written plan should include implementation dates. The plan will need to reference the requirements that owners or operators of emission sources will need to undertake to reduce pollution contributing to the air quality problems.                                                                                                                                                                                                                                                                                                          
• Involve the public. Invite input from the regulated community and others, including the general public when developing the control strategy. This early consultation reduces later challenges and can help streamline implementation.                                                                                                                                                            
• Incl ude compliance and enforcement programs.  These programs are very important to include and help owners or operators of sources understand the requirements, as well as the actions that environmental authorities can take if the sources don’t comply. 

​ Governments getting started in managing air quality should focus first on obvious sources of air pollution and the quickest means of controlling air emissions. More sophisticated and comprehensive strategies can be developed over time. The goal for all control strategies is to achieve real and measurable air emission reductions.

In the United States, control strategies to meet and maintain the national ambient air quality standards are developed by state governments. State governments adopt control measures through their legislative process and include them in state implementation plans, which need to be submitted and approved by EPA. The control measures are described and included in the plan.  Control measures that are part of an approved state implementation plan can be enforced by either the state or the national government.

Learn more regarding  basic information about air quality state implementation plans  and about  air quality implementation plans .

Learn more about how c ost analysis models and tools for air pollution regulations   support the assessment of emission reductions and engineering costs for air pollution control strategies.

Learn more about reducing emissions of hazardous air pollutants  and a ddressing stationary sources of air pollution  in the United States .

• Air Quality Management Process Home
• Overview of Air Quality Management
• Assessment and Implementation
• Tools and Resources

16 projects that could end air pollution around the world

Air pollution is terrible for human health and the planet. but, hopefully, the days of polluted air are numbered, all thanks to these 16 innovative global projects..

Christopher McFadden

1 ,  2

• Air pollution poses a severe risk worldwide.
• Towns and cities are choked with smog and dangerous emissions, damaging both the environment and the health of global populations.

However, we’re gradually developing ways to help solve this problem .

Air pollution is one of the banes of living in modern society. But, it turns out that we could someday end air pollution with cutting-edge technologies, government initiatives, and innovative projects. Here are some of the projects that might make a difference.

What are the leading causes of air pollution, and why is it a problem?

In short, the leading causes of air pollution are the expulsion of tiny solid and liquid particles into the atmosphere, solids such as soot, dust, and gases such as nitrogen dioxide, ozone, sulfur dioxide, and carbon monoxide. These can cause harm to people if they are inhaled and can also damage the environment.

Air pollution can stem from several sources, such as domestic consumption of wood and coal, vehicle exhausts, industrial outgassing, and natural sources, such as dust and wildfires. When particles from these sources become suspended in the air, they are technically called aerosols. 

These air contaminants are particularly bad for the environment and  human health . The health effects of air pollution include symptoms like:

• Irritation of the eyes, nose, and throat.
• Wheezing, coughing, chest tightness, and breathing difficulties.
• Existing lung and heart problems, such as asthma, are becoming worse.
• Increased risk of heart attack or even death.

ElizabethViera/Wikimedia

Air pollution also has some potentially severe effects on the environment too. Some common environmental impacts include: 

• Eutrophication.
• Poisoning of animals and plants.
• Ozone depletion in the stratosphere.
• Climate change.

For this reason, it is in everyone’s and every nation’s interest to keep track of pollutants and work to minimize their release as much as possible. The more potent aerosols are released into the atmosphere whenever fossil fuels are burned. But they also come from natural sources like volcanoes and forest fires. 

Aerosols can enter the atmosphere directly or form in the air through chemical reactions. Another seriously damaging air pollutant is ozone — the compound that constitutes the protective barrier around the Earth to stave off the worst effects of solar radiation. But when ozone reaches lower altitudes, it can be incredibly damaging to the environment and people’s health. 

Peter Griffin

According to NASA , “Ground-level ozone is created when sunlight reacts with certain chemicals that come from sources of burning fossil fuels, such as factories or car exhaust. When particles in the air combine with ozone, they create smog. Smog is a type of air pollution that looks like smoky fog and makes it difficult to see.”

Air pollution can also have a severe impact on the Earth’s climate too. Like those formerly mentioned, aerosols can directly impact how the Sun’s light hits the Earth’s surface.  Some aerosols , such as certain sulfates and nitrates, can reflect sunlight into space, while others, like black carbon, can absorb it. How these particles interact with sunlight depends entirely on physical properties like color and composition. 

Generally speaking, according to NASA , “Bright-colored or translucent particles tend to reflect radiation in all directions and back towards space. Darker aerosols can absorb significant amounts of light”.

This particular feature of air pollution can severely affect the Earth’s climate. For example, after the 1991 Mount Pinatubo eruption in the Philippines, more than 20 million tons of sulfur dioxide (SO2) and fine ash particulate were ejected into the Earth’s atmosphere.

Yabang Pinoy/Flickr

SO2 reacts with other atmospheric substances to form fine particulate sulfate aerosols. These tiny particles form high above the cloud level, around 37 miles (60 km) above, and can remain there for a very long time as they don’t get washed from the sky through precipitation. As a result, average global temperatures dropped by 1 degree Fahrenheit (0.6 degrees Celsius) for roughly two years. Interesting indeed, but is there anything that we can do to eliminate or at least mitigate the problems associated with air pollution ? Let’s take a look at some exciting proposals. 

What are some of the most exciting air pollution solutions?

And so, without further ado, here are some exciting solutions to air pollution . This list is far from exhaustive and is in no particular order. 

1. Friends of the Earth: letting citizens test their air quality

Friends of the Earth

One of the best tools in the fight against air pollution is education. By educating people on the importance of clean air, what they can do to lower their emissions, and how to be aware of the air quality in their area, the pollution problem can be better addressed.

Friends of the Earth is an environmental charity in the UK that has started supplying citizens with testing kits to learn more about the air quality in their local areas. The kits include a monitoring tube and an easy-to-follow guide, so concerned citizens can get accurate answers about the air they breathe.

2. The Nanjing vertical forest: growing an urban forest to clean the air

Stefano Boeri Architetti

Due to the heavily industrialized areas all across China, they’ve been suffering from some of the highest levels of air pollution worldwide. Thankfully, China proposed and implemented numerous pollution-busting initiatives these past few years to make their air healthy again.

One such project is the Nanjing Vertical Forest in Jiangsu province. It’s been estimated that the forest will be able to absorb 25 tons of carbon dioxide and release enough oxygen to make the air 3,000 times healthier than its current state. The design featured 3,000 different species of plants and was completed in 2018.

3. AIR-INK: printing with inks made from polluted air

Graviky Labs/Kickstarter

Some of the most exciting projects seeking to combat air pollution are also looking to utilize the pollutants drawn from the air creatively. One such project is AIR-INK  – an ink made from carbon emissions.

The product is made by Graviky Labs and was funded via Kickstarter. People have to connect the KAALINK device to their car exhaust pipe, and within 45 minutes of driving, they’ll have one fluid ounce (30 ml) of ink. The captured pollutants are then purified in a lab and manufactured into usable ink.

4. The smog-free tower: transforming smog into jewelry

Studio Roosegaarde

Ink is one thing, but what if you could turn pollution into glittering gems? Sounds too good to be true? Then look at the Smog-Free Tower , a vacuum that sucks in smog and condenses the particles into gemstones.

It’s the brainchild of Dutch artist Dan Roosegaarde. The Smog-Free Tower uses relatively little energy, sending positive ions into the air and connecting themselves to dust particles.

A negative ion in the vacuum draws the positive ions back inside, bringing the particles. The fine carbon particles the tower collects can be condensed to create tiny “gemstones” in jewelry like rings and cufflinks. Each tiny stone equals 265,000 gallons (1,000 cubic meters) of purified air.

The tower debuted in Rotterdam in 2015; it is now being used in other cities worldwide.

5. “Free” transport: encouraging citizens to ditch their cars

Standardizer/Wikimedia

By now, it’s common knowledge that our cars are some of the biggest culprits of polluting the air. That’s why Germany is considering making public transport free  to encourage citizens to reduce their carbon footprint by leaving their cars at home.

While a great initiative, it must be noted that such a project is not actually “free,” per se . They will be paid for indirectly through taxation . 

The announcement was made in February of 2018, and trials look set to occur throughout the country before the year ends. It’s a controversial suggestion and one that hasn’t convinced everyone. If they can pull it off, however, it could have a massive impact on the air quality in Germany. A 2019 survey revealed that 2/3rds of the public seems to favor this .

6. The world’s largest air purifier: cleaning the air with a skyscraper

CCTV/YouTube

In January 2018, work began on the world’s largest air purifier in Xian, China .

The massive structure measures 328 feet (100 meters) and can improve air quality within an almost 4-mile radius (10 square kilometers).

The tower is just one of the many Chinese efforts to combat air pollution . The future will determine how effective the tower is, and it won’t be surprising to see similar towers erected across the country if the results are positive.

7. Pollution vacuum cleaners: suck up the air’s contaminants

Evinity Group

What if we could place giant vacuum cleaners on buildings to clean the surrounding air? This question spurred the Envinity Group , a Dutch collective of inventors, into action. In 2016, they debuted an enormous industrial vacuum to remove airborne contaminants.

The vacuum removes fine and ultra-fine particles, which have been identified to be carcinogens by the World Health Organization. The inventors claim that the vacuum can eliminate 100% of fine particles and 95% of ultra-fine particles within a 984-foot radius (300 meters).

8. Fuel bans: taking fossil fuels off the roads for good

SounderBruce/Flickr

Removing contaminants from the air is great as a short-term solution, but it doesn’t address the long-term effects of carbon emissions. One, while arguably a draconian, way that many countries are looking to create a greener, cleaner future is through the banning of cars that use petrol and diesel.

The United Kingdom  is among the countries legislating to make the change. The government plans to effectively ban all new petrol and diesel vehicles from the road by 2035. With the rapidly growing interest in electric vehicles worldwide, initiatives like these have a high chance of succeeding. 

9. CityTree: purifying urban areas in the natural way

Green City Solutions

Urban areas are the worst hit when it comes to air pollution . The lack of green areas and trees in cities means there’s little opportunity for carbon dioxide to be absorbed, leaving the air quality poor. That’s why the German start-up, Green City Solutions, created the CityTree .

The CityTree is a vertical unit, like a billboard, incorporating moss and lichen. Thanks to these hard-working plants, each unit can absorb as much as 240 tons of carbon dioxide annually. This means they can perform the task of 275 trees while demanding a fraction of the space and cost.

10. All electric: setting the stage for zero-emissions vehicles

Jason Rogers/Flickr

When many countries finally successfully ban combustion engine vehicles from their roads, they’ll need a lot of electric cars to take their place. India, to name just one country, has announced that as of 2030 , they will only be selling electric vehicles.

This would be a massive game-changer for India, whose population currently suffers 1.2 million air pollution -related deaths yearly. The change could also save the country $60 billion in energy costs. The brave move is one that many other countries are sure to follow.

11. Fuel from pollutants: creating hydrogen fuel from air pollution

Today’s pollution could very well become tomorrow’s fuel. That’s thanks to research from the University of Antwerp and KU Leuven . In May 2017, scientists discovered a startling new method that allowed them to purify the air and simultaneously create hydrogen fuel from the extracted pollutants.

The researchers created a device containing a thin membrane. On one side of the membrane, the air was purified. On the other side, hydrogen gas resulting from the degradation of the contaminants was collected. The gas could then be used as fuel. The device was powered by solar energy, making it entirely clean.

12. Pollution sensors: providing data on air quality everywhere

Intel Free Press/Wikimedia

One issue that has stalled the fight against air pollution is a lack of comprehensive data. While urban areas are well-tested for air quality, suburban and rural areas have fewer resources when measuring air quality.

In India , government initiatives are installing pollution sensors across all areas of the country to detect and manage air pollution better. A new, cutting-edge series of sensors were certified in 2019 and has already provided valuable data in India’s fight against air pollution.

13. Smart streetlights and sensors:

Working in tandem to clean the air.

fklv (Obsolete hipster)/Flickr

India isn’t the only place looking to install state-of-the-art sensors. The Czechia announced that they would install carbon dioxide monitors inside the streets’ smart lights in its capital, Prague.

The sensors can provide real-time information on the worst affected areas regarding air pollution , allowing for more effective strategies in combating pollution and letting residents know which areas of the city are at the most significant risk to their health.

14. Anti-smog guns: shooting pollution down from the air

New Delhi Municipal Council/Twitter

The idea of an anti-smog gun might sound ridiculous, but it could effectively clear smog-afflicted areas during high pollution. The government of Delhi, India, tested the guns in 2017 and has since brought them online to help reduce the dangerous smog levels in Anand Vihar.

The guns work by spraying water vapor into the air, which absorbs the pollutants before falling to the ground like rain. While it doesn’t remove the contaminants entirely, it’s an effective short-term solution for smog-heavy days where breathing the air could present a severe health risk to residents.

15. Project air view: tracking pollution in your area

David McSpadden/Wikimedia Commons

Apparently, Google Earth is beneficial for creating accurate maps of the world and giving us insight into the quality of air. In a project launched by Google in 2015, Google Street View cars traveled around West Oakland, taking air samples. 

Through this, they could gather comprehensive data about air quality in the city and how it fluctuated over time. Thanks to this research, they could use the system to allow users to examine the average air quality in their and other areas worldwide.

Access to such information would allow for more effective targeting of anti-pollution initiatives. It would warn people about the more dangerous areas regarding poor air quality.

16. Check out the Mandragore Carbon Sink Tower

Designed by the architecture firm Rescubika , this fantastic concept project envisions a “green” residential tower on New York’s Roosevelt Island. Called Mandragore , the building pushes the envelope on the current limits of sustainability practices. 

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Its design is based on the mandrake plant and will be packed with many innovative energy-saving and carbon-capture technologies and strategies. It would use the best passive heating and cooling techniques to condition the interior space. It would incorporate as many natural materials as possible and a literal forest of plants and trees.

The scheme would have 1,600 trees and almost 300,000 square feet of living plant walls across its 160 levels in its current design.

And that’s all for now, folks. Will these solutions ring the death knell on human-created air pollution or not? Many of them are very promising. The future will show if they will significantly dent the air pollution problem. More innovation like this is always welcome to tackle the problem. 

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ABOUT THE EDITOR

Christopher McFadden Christopher graduated from Cardiff University in 2004 with a Masters Degree in Geology. Since then, he has worked exclusively within the Built Environment, Occupational Health and Safety and Environmental Consultancy industries. He is a qualified and accredited Energy Consultant, Green Deal Assessor and Practitioner member of IEMA. Chris&rsquo;s main interests range from Science and Engineering, Military and Ancient History to Politics and Philosophy.

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