**1. Introduction**

Over the last decade, numerous studies have shown that exposure to the current levels of human-caused air pollution can lead to a wide range of harmful health effects [1]. Current data makes it possible to give a rough estimate as to the number of health problems which can be directly attributed to air pollution in each territory and to detect the avoidable sources of such pollution. An assessment of the risks associated with human activities is an important tool for quantifying the current problem in terms of its size and how it is evolving, prior to being able to overcome such problems. Recent research shows that motor vehicles are a major contributor to air pollution [2] and sugges<sup>t</sup> that harmful effects

exist even at very low levels, with no clear evidence that there is a threshold below which pollution has no effects on people's health [3,4].

Several studies have analysed the environmental impact of the provision by primary care centres (PCCs) of various healthcare services, which up until now have been provided by hospitals or specialized services [5,6], thus avoiding the patient's need to travel to a specialized service [6–8]. However, the potential impact of conducting ultrasound scans in PCCs with regard to pollutant emissions has not previously been studied. At a time of growing interest in reducing the environmental impact of health-related activities [9], this study assesses the impact of conducting ultrasound scans in PCCs as a means to reduce the environmental footprint of this process. Nevertheless, the need for a medical test, such as an ultrasound, can be affected by geographical barriers, and often the distance which users need to travel can cause particular problems, especially for patients in rural communities or places where there is an insufficient number of doctors or deficiencies in the provision of health services [10,11].

Given these circumstances, in recent years ultrasound equipment has been introduced in PCCs to be used by a group of family medicine professionals with special training, fostering a programme of continuous training and an increasing volume of activity. For several years, Catalonia, alongside other autonomous communities, has been committed to equipping healthcare centres with ultrasound scanners and training their staff in how to use them. This study examines the model applied in the Central region of Catalonia, in Osona county, where for some years now [12] ultrasound equipment has been gradually introduced into primary care (PC), beginning with the centres which were the most willing to use them. During this time, the staff has received training in its usage.

This new ultrasound scan service means patients can visit their general practitioner (GP) to have their test done instead of having to go to the nearest radiology service in the county and waiting for an appointment. Although patients in urban areas live quite close to their referral hospital's radiology service, this type of service is especially valuable in rural areas where patients find it more difficult to reach the hospital [13]. As a result, the various professional bodies and groups which represent GPs support the use of ultrasound scans in a large number of clinical situations which form part of routine PC since it increases their ability to diagnose and treat cases, optimizing the use of referrals for diagnostic tests and reducing waiting times [14]. Furthermore, having such tests carried out in PC is well received by both users and healthcare professionals [15]. Nevertheless, few studies have been published which study this phenomenon in rural areas [16] and/or in PC [12], despite many scientific organisations offering training in this field.

In spite of the fact that the carrying out of ultrasound scans in PCCs may be seen as a novelty [17], Hahn et al. published a study examining the education and training received by family physicians more than 30 years ago [18], demonstrating that such programmes were cost-effective and provided quality care [19].

The potential for non-radiologists to perform ultrasound scans, what is known as the point-of-care ultrasound (POCUS) model [8], means the technique can actually form part of the consultation, giving it grea<sup>t</sup> potential for a timely evaluation and a speedy diagnosis. This in turn makes it highly appealing to GPs, who have increasingly undergone the necessary training to provide this service. The use of ultrasound scans at the patient's bedside is providing a speedy service to thousands of users [16], avoiding unnecessary travel to specialized services, while representing potential economic savings (environmentally beneficial) for each face-to-face consultation avoided.

Local air pollution and global climate change policies should work together to maximize the benefits of lowering air pollution levels. Evidence suggests that more in-depth cross-city studies have the potential to highlight best practices in both local and global terms [2]. Moreover, as a mobile business, the healthcare sector consumes countless liters of fossil fuels when patients and medical professionals travel to and from their appointments, to pick up prescriptions, or collect test results [20]. The healthcare sector, which has a special focus on health promotion, can thus reasonably be expected to have a moral obligation to set a good example. Ostrom argues that local initiatives are indeed the

ones that have the greatest global impact [21]. Hence, potential local mitigation strategies relevant to the health sector are potentially transferable to other countries.

This study focused on the relatively unexplored use of POCUS as a health sector climate change mitigation and adaptation strategy, evaluating its different uses in rural and urban environments. Overall, this is an example of the growing concern of primary care centers with air pollution affecting their local communities.

#### **2. Materials and Methods**

This is a retrospective study using administrative data of patients who underwent an ultrasound examination in 2019 by one of the eight GPs of the five primary care centres (PCCs) belonging to the Catalan Institute of Health in Osona county. Of these five centres, two were urban and three rural.

The radiology referral service for all of the patients in the PCCs involved in the study was located in the capital of the region, Vic (Figure 1).

**Figure 1.** Map showing the primary care centres and their associated diagnostic imaging service in Osona.

This study employed the Primary Care Information System's [22] criteria to differentiate between urban and rural centres. It defines as rural those PCCs which have an assigned population density of less than 150 inhabitants/km<sup>2</sup> and less than 10,000 inhabitants [23].

Using the data regarding ultrasound scans, their impact on the journeys undertaken by users in their own vehicles was estimated in terms of the associated costs and the resulting reduction of air pollution. Distances avoided or not travelled were calculated in terms of return journeys from the PCC to the radiology referral service.

The reduction in the emissions of air pollution and greenhouse gases was calculated by multiplying the kilometres avoided by the corresponding emissions of each pollutant. The economic costs saved were derived from calculating the difference between the cost of traveling to the radiology referral service and that of traveling to the nearest PCC. Finally, the time saved was defined as the sum of the duration of the return journey to the radiology referral service. Data from Google Maps was used in order to calculate the distances travelled and the time saved on the journey using the

existing road network. The search option "fastest route with the usual tra ffic" was employed in all instances. To calculate fuel consumption we used the average cost and consumption of a small family car, with fewer than three passengers with no luggage or additional luggage systems, being driven smoothly with an average fuel consumption of 6.9 L/km. The cost of fuel was calculated by averaging the cost of a liter of Gasoline SP95, Gasoline SP98, Diesel A, Diesel A+ and Biodiesel, which are the most commonly used fuels in motor vehicles. Road tra ffic emissions depend on many factors, such as the type of vehicle (passenger cars, light duty vehicles, heavy duty vehicles, mopeds and motorcycles), the speed at which they travel, the distance travelled, the type of fuel, the engine displacement and weight, the age of the vehicle and the technology it uses for the reduction of NOx. In order to calculate the emissions for the study, it was considered that routes involving urban roads have an average speed of 30 km/h, secondary roads of 60 km/h, and that on main roads all vehicles travel at 120 km/h.

The main air pollutants analysed included NOx, SOx, O3, CO, NH3 and VOC. The emission of suspended particles (PM) which have a demonstrable impact on health was also calculated [24]. Particles smaller than 30 μm in diameter have an impact on the nose and throat, while those less than 10 μm, such as SO2, NO2 and ozone, have an impact on the trachea, bronchi and bronchioles. For these calculations, emission factors have been used according to the number of licensed vehicles in Catalonia in 2012 and the 2013 guide to calculating emissions of atmospheric pollutants [25]. Said guide is based on the COPERT 4 v10.0 software program which includes the emission factors described in the European Monitoring and Evaluation Programme (EMEP)/European Environment Agency (EEA) air pollutant emission inventory guidebook [26]. COPERT 4 v10.0 is a tool developed by Aristotle University of Thessaloniki and funded by the European Environment Agency [27].

The emission factor used in the study was an average emission factor which takes into account tra ffic for all types of road and is expressed in g/km. The calculation of emissions was carried out using the formula E = M × N × EF; where E is the emission of the pollutant (g), N is the number of vehicles, M is the distance travelled by the vehicle (km) and EF is the emission factor (g/km). The emission of air pollutants per km is shown in Table 1.


**Table 1.** Emission of pollutants specific to private vehicles (per passenger and per km).

1 EF: Emission Factor = Emissions (g)/number of vehicles × distance travelled (km). Source: 2013 guide to calculating emissions of atmospheric pollutants [25].

It was considered that an ultrasound scan conducted in a PCC avoided a face-to-face consultation with the radiology service when no subsequent face-to-face visit was made to the service in relation to the same type of ultrasound test in the three months following the ultrasound test conducted by the health centre [6,28].

Although the study focuses on the analysis of the environmental impact derived from the direct displacement of patients, to have a more complete picture we have included impact as a consequence of the mobility of professionals. There are multiple players who can participate in the ultrasound

diagnostic process. Air pollution is a mixture of different pollutants and we cannot add up the risk for those pollutants. Epidemiological studies usually rely on a single marker of air quality. As in other previous studies [29], we have selected PM10 as the marker of air pollution. The population exposure to PM10 was represented by an average population-weighted concentration derived from PM10 concentration tables developed by local authorities.

A descriptive analysis of the different types of ultrasound scans conducted by the centres was carried out for the study according to whether the health centres were urban or rural, and by comparing those tests which required subsequent evaluation by the radiology referral service. The differences between centres were analysed based on the average cost per patient journey and on the average quantity of pollutants emitted in undertaking said journey. The data was processed and analysed using Microsoft Excel and SPSS 23.0 (SPSS Inc., Chicago, IL, USA) programs.
