Size of government and willingness-to-pay for environmental policy: Evidence from a cross-country survey.

Citizen support is an important precursor to climate change mitigation polices. Public opinion can shape public policy and vice versa. This paper uses the 2010 International Social Survey Programme (ISSP) Environment Module to investigate cross-national differences in support for climate policy. We introduce size of government, measured by government revenues as a share of GDP, as a new country-level factor. Our sample includes 31,511 responses from 33 countries. We use multilevel models to estimate the relationship between country-level factors and environmental policy support, conditional on a series of individual factors. Increasing the size of government by one standard deviation reduces support for environmental policy by 0.13 points on a 5-point scale. For comparison, a one standard deviation increase in GDP per capita leads to a 0.24 increase in support and a one standard deviation increase in air pollution leads to a 0.13 point increase. The implication for environmental policy is that high tax countries have an aversion to price and tax increases aimed at protecting the environment. We conclude that use of taxes for environmental policy must include clear expectations for how revenues will be recycled or how other taxes will be lowered if they are to gain widespread support.

Laboratory Comparison of Low-Cost Particulate Matter Sensors to Measure Transient Events of Pollution-Part B-Particle Number Concentrations.

Low-cost Particulate Matter (PM) sensors offer an excellent opportunity to improve our knowledge about this type of pollution. Their size and cost, which support multi-node network deployment, along with their temporal resolution, enable them to report fine spatio-temporal resolution for a given area. These sensors have known issues across performance metrics. Generally, the literature focuses on the PM mass concentration reported by these sensors, but some models of sensors also report Particle Number Concentrations (PNCs) segregated into different PM size ranges. In this study, eight units each of Alphasense OPC-R1, Plantower PMS5003 and Sensirion SPS30 have been exposed, under controlled conditions, to short-lived peaks of PM generated using two different combustion sources of PM, exposing the sensors' to different particle size distributions to quantify and better understand the low-cost sensors performance across a range of relevant environmental ranges. The PNCs reported by the sensors were analysed to characterise sensor-reported particle size distribution, to determine whether sensor-reported PNCs can follow the transient variations of PM observed by the reference instruments and to determine the relative impact of different variables on the performances of the sensors. This study shows that the Alphasense OPC-R1 reported at least five size ranges independently from each other, that the Sensirion SPS30 reported two size ranges independently from each other and that all the size ranges reported by the Plantower PMS5003 were not independent of each other. It demonstrates that all sensors tested here could track the fine temporal variation of PNCs, that the Alphasense OPC-R1 could closely follow the variations of size distribution between the two sources of PM, and it shows that particle size distribution and composition are more impactful on sensor measurements than relative humidity.

Slouching or speeding toward net zero? Evidence from COVID-19 energy-related stimulus policies in the G20.

This paper analyzes the size and nature of green fiscal stimulus in the G20 countries in response to the COVID-19 crisis, with a focus on the energy-related policies. We exploit a new dataset, the Energy Policy Tracker (EPT), with detailed information on countries' policies since the start of the pandemic. Between January 2020 and December 2021, G20 countries enacted 913 stimulus measures that have direct impacts on energy supply and demand. The average country spent $395 USD per person on energy-related policies. Only 30% of this amount, on average, is devoted to low-carbon measures, mostly in the transit and buildings sectors, with considerable variation across countries. To properly compare countries' efforts in aligning their COVID-19 stimulus with climate goals, we construct a new index, the Green Energy Policy Index (GEPI), using principal components analysis, taking into account both "green" and "brown" stimulus measures. The GEPI varies considerably across countries. We find that on average, countries with a "greener" energy-related stimulus are wealthier and have a lower emission intensity. On average, countries that have experienced the crisis more acutely, both in terms of deaths and gross domestic product (GDP) loss, have "greener" stimulus packages. We discuss the implications of these findings for future research and climate energy policy-making.

Effectiveness of SMS reminders on improving follow-up rate of hypertensive patients during COVID-19 pandemic: An interim analysis of randomized controlled trial

Background@#Non-communicable diseases are a challenge to manage, more so during the COVID-19 pandemic. SMS-text messaging can be part of the solution, although more studies are needed.@*Objective@#Researchers evaluated the effectiveness of sending SMS reminders on different time intervals from the scheduled follow-up among hypertensive patients during the COVID-19 pandemic.@*Methods@#This is an interim analysis using a multi-clinic, three-armed, blinded, randomized controlled trial. 65 participants from two primary care facilities were recruited. Group A and B were sent SMS reminders three days and one day prior to their follow up appointment, respectively. Participants randomized to group C were not sent SMS reminders. Primary outcome measured was the difference between the follow-up rates of the three study arms. Intention to treat analysis was done.@*Results@#Follow-up rates for groups A, B, and C were 23.81%, 6.25%, and 19.05% respectively. Compared to the control group, participants in group A were likely to follow-up, while group B were less likely to follow-up (RR= 0.94 and 1.16 respectively). Comparing the two treatment arms, group A showed 19% risk reduction in non-attendance compared to group B (RR=0.81). The researchers failed to demonstrate statistical significance (p = 0.361024) between the three study arms.@*Conclusion@#This interim analysis shows a possible benefit of sending SMS reminders three days before scheduled follow-up. More robust conclusion can be made once more participants are added to the study. Longer time interval for sending SMS reminders, longer follow-up schedule, and broader inclusion criteria are recommended for future studies.

Laboratory Comparison of Low-Cost Particulate Matter Sensors to Measure Transient Events of Pollution.

Airborne particulate matter (PM) exposure has been identified as a key environmental risk factor, associated especially with diseases of the respiratory and cardiovascular system and with almost 9 million premature deaths per year. Low-cost optical sensors for PM measurement are desirable for monitoring exposure closer to the personal level and particularly suited for developing spatiotemporally dense city sensor networks. However, questions remain over the accuracy and reliability of the data they produce, particularly regarding the influence of environmental parameters such as humidity and temperature, and with varying PM sources and concentration profiles. In this study, eight units each of five different models of commercially available low-cost optical PM sensors (40 individual sensors in total) were tested under controlled laboratory conditions, against higher-grade instruments for: lower limit of detection, response time, responses to sharp pollution spikes lasting <1 min , and the impact of differing humidity and PM source. All sensors detected the spikes generated with a varied range of performances depending on the model and presenting different sensitivity mainly to sources of pollution and to size distributions with a lesser impact of humidity. The sensitivity to particle size distribution indicates that the sensors may provide additional information to PM mass concentrations. It is concluded that improved performance in field monitoring campaigns, including tracking sources of pollution, could be achieved by using a combination of some of the different models to take advantage of the additional information made available by their differential response.

2-Pyridylfuran: a new fluorescent tag for the analysis of carbohydrates.

We herein report the use of 1,3-di(2-pyridyl)-1,3-propanedione (DPPD) as a fluorogenic labeling reagent for sugars. Reaction of DPPD with the anomeric carbon affords a fluorescent 2-pyridylfuran (2-PF) moiety that permits the sensitive HPLC-based detection of monosaccharides. 2-PF-labeled monosaccharides can be easily separated and analyzed from mixtures thereof, and the reported protocol compares favorably with established labeling reagents such as 2-aminobenzoic acid (2-AA) and 1-phenyl-3-methyl-5-pyrazolone (PMP), ultimately allowing subfemtomole detection of the galactose-derived product. Furthermore, we demonstrate the application of DPPD in the labeling of monosaccharides in complex biological matrices such as blood and milk samples. We envisage that DPPD will prove to be an excellent choice of labeling reagent in monosaccharide and carbohydrate analysis.

Automated flow injection analyzer with on-line solid-phase extraction and chemiluminescence detection for the determination of dodecylamine in diesel fuels.

This paper describes the development of a portable, automated flow injection-chemiluminescence (FI-CL) analyzer incorporating on-line solid-phase extraction (SPE) for the determination of dodecylamine (detergent) in diesel fuels. The method is based on the peroxyoxalate/sulforhodamine 101 chemiluminescence reaction, with SPE required to remove indigenous compounds within the diesel fuel matrix that interfere with the CL response. The automated analyzer achieved a detection limit of 2.9 mg L(-1) and a linear range of 2.9-50 mg L(-1), which was suitable for determinations of dodecylamine at levels typically present in fully formulated diesel fuels (40 mg L(-1)). Analyses of base fuels from five different sources demonstrated that an automated FI-CL-SPE system could provide a portable instrument for monitoring the presence/absence of dodecylamine in diesel fuels.