The impact of urban air pollution on the environments and human health has drawn increasing concerns from researchers, policymakers and citizens. To reduce the negative health impact, it is of great importance to measure the air pollution at high spatial resolution in a timely manner. Traditionally, air pollution is measured using dedicated instruments at fixed monitoring stations, which are placed sparsely in urban areas. With the development of low-cost micro-scale sensing technology in the last decade, portable sensing devices installed on mobile campaigns have been increasingly used for air pollution monitoring, especially for traffic-related pollution monitoring. In the past, some reviews have been done about air pollution exposure models using monitoring data obtained from fixed stations, but no review about mobile sensing for air pollution has been undertaken. This article is a comprehensive review of the recent development in air pollution monitoring, including both the pollution data acquisition and the pollution assessment methods. Unlike the existing reviews on air pollution assessment, this paper not only introduces the models that researchers applied on the data collected from stationary stations, but also presents the efforts of applying these models on the mobile sensing data and discusses the future research of fusing the stationary and mobile sensing data.

https://www.mdpi.com/2220-9964/6/12/389/pdf

A review of urban air pollution monitoring and exposure assessment methods

A steady trend towards the design of mostly-digital and digital-friendly analog circuits, suitable to integration in mainstream nanoscale CMOS by a highly automated design flow, has been observed in the last years to address the requirements of the emerging Internet of Things (IoT) applications. In this context, this tutorial brief presents an overview of concepts and design methodologies that emerged in the last decade, aimed to the implementation of analog circuits like Operational Transconductance Amplifiers, Voltage References and Data Converters by digital circuits. The current design challenges and application scenarios as well as the future perspectives and opportunities in the field of digital-based analog processing are finally discussed.

Re-Thinking Analog Integrated Circuits in Digital Terms: A New Design Concept for the IoT Era

Accurate detection of hydrogen gas in vehicle interiors is very important for the future of a fuel cell car. Since this type of gas is highly volatile and flammable, the measurement methods have to be very reliable and precise due to safety reasons. In this paper a thermal conductivity sensor for hydrogen gas detection is presented, exhibiting a lower detection limit of 2000 ppm hydrogen in laboratory air. The sensor element is realized by micro-fabrication techniques on silicon wafers. The heated filament is exposed by a selective wet etching process creating a micro-hotplate on a thin membrane. In order to minimize power consumption, the sensor is operated in pulsed mode. Hydrogen gas detection was carried out using a synthetic gas testbench. Measurements of hydrogen contents ranging from 0% to 4% with an increment of 0.5% were successfully performed for ambient gas temperatures between − 15 ° C and 84 ° C. Including humidity, high moisture contents have the greatest influence on thermal conductivity. This was predicted in theoretical investigations and confirmed in experiments. For evaluation, both the change in resistance Δ R as well as the time constant τ were taken as sensor output. For both quantities, the previously established theoretical relationship with thermal conductivity could be confirmed.

MEMS-based thermal conductivity sensor for hydrogen gas detection in automotive applications

As an important member of the optical fiber sensor family, long period fiber gratings (LPFG) have attracted increased attention due to their outstanding characteristics. The LPFG is a transmission ...

Mini review: Recent advances in long period fiber grating biological and chemical sensors

This paper presents an energy-efficient intelligent multisensor system for hazardous gases, whose performance can be adaptively optimized through a multimode structure and a learning-based pattern recognition algorithm. The multimode operation provides control capability on the tradeoff relationship between accuracy and power consumption. In-house microelectro-mechanical (MEMS) devices, with a suspended nanowire structure, are manufactured to provide desired characteristics of small size, low power, and high sensitivity. Pattern recognition to combine the dimensionality reduction and the neural network is adopted to improve the selectivity of MEMS gas sensors. Moreover, potential deviations in sensing characteristics are calibrated through a proposed self-calibration zooming structure. Reconfigurable circuits for these key features are integrated into an adaptive readout integrated circuit which is fabricated in a 180-nm complementary metal-oxide semiconductor process. For its system-level verification, a wireless multichannel gas-sensor system prototype is implemented and experimentally verified to achieve 2.6 times efficiency improvement.

An Energy-Efficient Multimode Multichannel Gas-Sensor System With Learning-Based Optimization and Self-Calibration Schemes

This paper reports a readout circuit for a resistive CO2 sensor, which operates by measuring the CO2-dependent thermal conductivity of air. A suspended hot-wire transducer, which acts both as a resistive heater and temperature sensor, exhibits a CO2-dependent heat loss to the surrounding air, allowing CO2 concentration to be derived from its temperature rise and power dissipation. The circuit employs a dual-mode incremental delta-sigma ADC to digitize these parameters relative to those of an identical, but isolated, reference transducer. This ratiometric approach results in a measurement that does not require precision voltage or power references. The readout circuit uses dynamically-swapped transducer pairs to cancel their baseline-resistance, so as to relax the required dynamic range of the ADC. In addition, dynamic element matching (DEM) is used to bias the transducer pairs at an accurate current ratio, making the measurement insensitive to the precise value of the bias current. The readout circuit has been implemented in a standard 0.16 $\mu \text {m}$ CMOS technology. With commercial resistive micro-heaters, a CO2 sensing resolution of about 200 ppm ( $1\sigma $ ) was achieved in a measurement time of 30 s. Similar results were obtained with CMOS-compatible tungsten-wire transducers, paving the way for fully-integrated CO2 sensors for air-quality monitoring.

/pdf/a-ratiometric-readout-circuit-for-thermal-conductivity-based-493aa2tidv.pdf

A Ratiometric Readout Circuit for Thermal-Conductivity-Based Resistive CO 2 Sensors

This paper presents a readout circuit for a carbon dioxide (CO2) sensor that measures the CO2-dependent thermal time constant of a hot-wire transducer. The readout circuit periodically heats up the transducer and uses a phase-domain $\Delta \Sigma $ modulator to digitize the phase shift of the resulting temperature transients. A single resistive transducer is used both as a heater and as a temperature sensor, thus greatly simplifying its fabrication. To extract the transducer’s resistance, and hence its temperature, in the presence of large heating currents, a pair of transducers is configured as a differentially driven bridge. The transducers and the readout circuit have been implemented in a standard 0.16- $\mu \text{m}$ CMOS technology, with an active area of 0.3 and 3.14 mm2, respectively. The sensor consumes 6.8 mW from a 1.8-V supply, of which 6.3 mW is dissipated in the transducers. A resolution of 94-ppm CO2 is achieved in a 1.8-s measurement time, which corresponds to an energy consumption of 12 mJ per measurement, >10 $\times $ less than prior CO2 sensors in CMOS technology.

/pdf/a-phase-domain-readout-circuit-for-a-cmos-compatible-hot-2j7apytfxl.pdf

A Phase-Domain Readout Circuit for a CMOS-Compatible Hot-Wire CO 2 Sensor

This paper reports a CO 2 sensor intended for indoor air-quality sensing. Both the thermal-conductivity-based CO 2 transducer and its readout circuit have been realized in 0.16µm CMOS technology. The readout circuit, based on an incremental ΔΣ ADC, employs ratiometric measurements to circumvent the need for a stable power reference. The sensor achieves 228ppm (1σ) CO 2 resolution in a 70s measurement time, while consuming 11.2mW from a 1.8V supply. This resolution is 2x better than that of state-of-the-art thermal-conductivity-based CO 2 sensors, thus facilitating the realization of fully-integrated CO 2 sensors for air-quality monitoring, and a significant reduction in their cost (>10x) and volume (>100x) compared with the non-integrated CO 2 sensors.

An integrated carbon dioxide sensor based on ratiometric thermal-conductivity measurement

This paper reports a readout circuit capable of accurately measuring not only the resistance of a resistive transducer, but also the power dissipated in it, which is a critical parameter in thermal flow sensors or thermal-conductivity sensors. A front-end circuit, integrated in a standard CMOS technology, sets the voltage drop across the transducer, and senses the resulting current via an on-chip reference resistor. The voltages across the transducer and the reference resistor are digitized by a time-multiplexed high-resolution analog-to-digital converter (ADC) and post-processed to calculate resistance and power dissipation. To obtain accurate resistance and power readings, a voltage reference and a temperature-compensated reference resistor are required. An accurate voltage reference is constructed algorithmically, without relying on precision analog signal processing, by using the ADC to successively digitize the base–emitter voltages of an on-chip bipolar transistor biased at several different current levels, and then combining the results to obtain the equivalent of a precision curvature-corrected bandgap reference with a temperature coefficient of 18 ppm/°C, which is close to the state-of-the-art. We show that the same ADC readings can be used to determine die temperature, with an absolute inaccuracy of ±0.25 °C (5 samples, min–max) after a 1-point trim. This information is used to compensate for the temperature dependence of the on-chip polysilicon reference resistor, effectively providing a temperature-compensated resistance reference. With this approach, the resistance and power dissipation of a 100 $\Omega $ transducer have been measured with an inaccuracy of less than $\pm 0.55~\Omega $ and ±0.8%, respectively, from −40 °C to 125 °C.

/pdf/a-cmos-readout-circuit-for-resistive-transducers-based-on-25u5onqbs9.pdf

A CMOS Readout Circuit for Resistive Transducers Based on Algorithmic Resistance and Power Measurement

The measurement of carbon-dioxide (CO2) concentration is very important in home and building automation, e.g. to control ventilation in energy-efficient buildings. This application requires compact, low-cost sensors that can measure CO 2 concentration with a resolution of 2 sensors require components that are CMOS-incompatible, difficult to miniaturize and power-hungry [1]. Due to their CMOS compatibility, thermal-conductivity-based sensors are an attractive alternative [2,3]. They exploit the fact that the thermal conductivity (TC) of CO 2 is lower than that of the other constituents of air, so that CO2 concentration can be indirectly measured via the heat loss of a hot wire to ambient. However, this approach requires the detection of very small changes in TC (0.25 ppm per ppm CO2 [3]).

Zeyu Cai

Papers

A Ratiometric Readout Circuit for Thermal-Conductivity-Based Resistive CO 2 Sensors

A Phase-Domain Readout Circuit for a CMOS-Compatible Hot-Wire CO 2 Sensor

An integrated carbon dioxide sensor based on ratiometric thermal-conductivity measurement

A CMOS Readout Circuit for Resistive Transducers Based on Algorithmic Resistance and Power Measurement

A phase-domain readout circuit for a CMOS-compatible thermal-conductivity-based carbon dioxide sensor