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The issue of sustainability is at the top of the political and societal agenda, being considered of extreme importance and urgency. Human individual action impacts the environment both locally (e.g., local air/water quality, noise disturbance) and globally (e.g., climate change, resource use). Urban environments represent a crucial example, with an increasing realization that the most effective way of producing a change is involving the citizens themselves in monitoring campaigns (a citizen science bottom-up approach). This is possible by developing novel technologies and IT infrastructures enabling large citizen participation. Here, in the wider framework of one of the first such projects, we show results from an international competition where citizens were involved in mobile air pollution monitoring using low cost sensing devices, combined with a web-based game to monitor perceived levels of pollution. Measures of shift in perceptions over the course of the campaign are provided, together with insights into participatory patterns emerging from this study. Interesting effects related to inertia and to direct involvement in measurement activities rather than indirect information exposure are also highlighted, indicating that direct involvement can enhance learning and environmental awareness. In the future, this could result in better adoption of policies towards decreasing pollution.

The issue of sustainability is at the top of the political and societal agenda, being considered of extreme importance and urgency. Human individual action impacts the environment both locally (e.g., local air/water quality, noise disturbance) and globally (e.g., climate change, resource use). Urban environments represent a crucial example, with an increasing realization that the most effective way of producing a change is involving the citizens themselves in monitoring campaigns (a citizen science bottom-up approach). This is possible by developing novel technologies and IT infrastructures enabling large citizen participation. Here, in the wider framework of one of the first such projects, we show results from an international competition where citizens were involved in mobile air pollution monitoring using low cost sensing devices, combined with a web-based game to monitor perceived levels of pollution. Measures of shift in perceptions over the course of the campaign are provided, together with insights into participatory patterns emerging from this study. Interesting effects related to inertia and to direct involvement in measurement activities rather than indirect information exposure are also highlighted, indicating that direct involvement can enhance learning and environmental awareness. In the future, this could result in better adoption of policies towards decreasing pollution. ; European Commission/EU RD/IST-265432 ; SONY-CS Computer Science Lab

Air is one of the most important elements of life for living things in the world. For humans, the air is an element that is very concerned because it is related to health. In the city of Semarang, the Air Pollution Standard Index (ISPU) at the KLHK station (Ministry of Life and Environment) Semarang City recorded a PM 10 of 7 while the air quality in Jakarta was monitored by the Air Quality Index (AQI) of 67 with parameters in the form of very small pollutant particles with a diameter less than 2.5 micrometres (PM 2.5). The Indonesian government has made efforts to reduce the air pollution index, such as reducing the number of vehicles with odd-even systems, users of environmentally friendly transportation modes such as BRT and Trans Central Java and clearing green lands in the middle of the city. The purpose of this research is how we make a tool that can determine the quality of the air around us and can be carried (portable) anywhere easily. Following the 4.0 industrial revolution that everything has been integrated with the Internet of Things (IoT) technology where the community can find out the air condition in real-time. In this research, later using the prototype method as a test. The main components are sensors consisting of MQ-6 (CO2 and smoke), MQ-7 (CO, LPG, CH4), MQ135 (Butane, AirQuality), and DHT-11 (Humidity, temperature) From the research that has been done where the air quality in urban areas has a low air quality index by measuring using a prototype consisting of a gas sensor and Arduino microntroller, which has been made to produce an average CO2 of 25 ppm, CO 2330 which has exceeded the threshold, while NH3 1.23 and C4H10 1120 are still below the threshold. These values are influenced by pollutants generated by transportation such as motorbikes, cars, and land transportation.

Air pollution is one of the biggest threat for the environment and the human's health. The monitoring of air pollution based on several atmospheric pollutants is becoming critical in most countries including Malaysia. This paper presents a development and enhancement features of real-time Internet of Things (IoT)-based environmental monitoring system for air quality. The proposed system will be beneficial to monitor the real-time data for a specific set of air quality parameters such as temperature, humidity and concentration of carbon monoxide, liquified petroleum gas (LPG) and smoke. An alarm system will be triggered if the concentration of carbon monoxide exceeds 50 ppm. Users can use their smartphone to view these data via Wi-Fi by installing an application called "AirProp". Based on the collected data, this paper also analyses other contributing factors such as time and traffic condition on the temperature, humidity and concentration of pollutant gases at different locations. The advantage of the real-time system is it serves as the data base platform to store data up to certain duration of time. The data can be further analysed and leveraged by governments and researchers to mitigate air pollution.

Particle matter is one of the criteria air pollutants which have the most considerable effect on human health in cities. Its legislation and regulation are mostly based on mass. We showed here that the total number of particles and the particle number concentrations in different size fractions seem to be efficient quantities for air quality monitoring in urbanized areas. Particle number concentration (N) measurements were realized in Budapest, Hungary, for nine full measurements years between 2008 and 2021. The datasets were complemented by meteorological data and concentrations of criteria air pollutants. The annual medians of N were approximately 9 × 103 cm−3. Their time trends and diurnal variations were similar to other large continental European cities. The main sources of N are vehicle road traffic and atmospheric new aerosol particle formation (NPF) and consecutive growth events. The latter process is usually regional, so it appears to be better assessible for contribution quantification than mass concentration. It is demonstrated that the relative occurrence frequency of NPF was considerable, and its annual mean was around 20%. NPF events increased the contribution of ultrafine (UF < 100 nm) particles with respect to the regional particle numbers by 12% and 37% in the city center and in the near-city background, respectively. The pre-existing UF concentrations were doubled on the NPF event days.