Forest regeneration on European sheep pasture is an economically viable climate change mitigation strategy

Livestock production uses 37% of land globally and is responsible for 15% of anthropogenic greenhouse gas emissions. Yet livestock farmers across Europe receive billions of dollars in annual subsidies to support their livelihoods. This study evaluates whether diverting European subsidies into the restoration of trees on abandoned farmland represents a cost-effective negative-emissions strategy for mitigating climate change. Focusing on sheep farming in the United Kingdom, and on natural regeneration and planted native forests, we show that, without subsidies, sheep farming is not profitable when farmers are paid for their labour. Despite the much lower productivity of upland farms, upland and lowland farms are financially comparable per hectare. Conversion to 'carbon forests' is possible via natural regeneration when close to existing trees, which are seed sources. This strategy is financially viable without subsidies, meeting the net present value of poorly performing sheep farming at a competitive $4/tCO2eq. If tree planting is required to establish forests, then ~$55/tCO2eq is needed to break-even, making it uneconomical under current carbon market prices without financial aid to cover establishment costs. However, this break-even price is lower than the theoretical social value of carbon ($68/tCO2eq), which represents the economic cost of CO2 emissions to society. The viability of land-use conversion without subsidies therefore depends on low farm performance, strong likelihood of natural regeneration, and high carbon-market price, plus overcoming potential trade-offs between the cultural and social values placed on pastoral livestock systems and climate change mitigation. The morality of subsidising farming practices that cause high greenhouse gas emissions in Europe, whilst spending billions annually on protecting forest carbon in less developed nations to slow climate change is questionable

Grill workers and air pollution health effects from charcoal combustion in Vientiane capital

Introduction: Grilled street foods are popular in urban communities in Lao People's Democratic Republic (Lao PDR). Charcoal is the main fuel used for, posing a risk of elevated exposure to toxic pollutants. This study explored levels of cooking-related pollutants from grilled food business and workers’ health effects. Materials and methods: A quantitative approach using multiple techniques was conducted during March and April 2022 in Vientiane Capital, Lao PDR. Methods included pollutant emission estimation from charcoal-combusting grill shops/street-carts and Particulate Matter (PM2.5 ) measurement, and examined the exposure and health effects among grill workers. Multiple sampling techniques were applied to identify study samples. Respiratory symptoms were the health effect of interest among grill workers. Results: Estimated emission of pollutants was over 75 tons/year from grill shops. Average PM2.5 level was 84.8 μg/m3 (21.6-254.8 μg/m3); which is above standard limits. A very high level of PM2.5 was found in grill markets. Most grill workers were female, worked 6-7 days/week, at least 8 h/day. Factors contributing to the presence of respiratory symptoms among grill workers were female gender, low income, indoor grilling, more years of grill-work, experience of intense smoke-cough, self-reliance on health and cigarette smoking. Conclusion: Grilling contributes to ambient air pollution, posing potential adverse environmental and public health impacts. Grill workers are likely to be exposed to high levels of all forms of air pollutants from street food grilling. Effective strategies are required to better protect grill workers from the effect of exposure to these harmful toxins and minimize the negative impacts on their health.</p

Air pollutant emissions and sources in Lao People’s Democratic Republic a provincial scale analysis for years 2013-2019

Recent rapid economic development in Lao People’s Democratic Republic (PDR) has increased national fuel consumption, vehicle fleet, industrial output, waste generation, and agricultural production. This has contributed to national average ambient fine particulate matter (PM2.5) air pollutant levels that are four times higher than World Health Organisation guidelines. Emission inventories are a key tool in understanding the major sources to these air pollution levels, and provide a starting point to identify where mitigation action can be targeted. A national air pollutant emission inventory has not been developed in Lao PDR and, combined with a limited air quality monitoring network means there is limited capacity to develop and track the effectiveness of mitigation actions. This study describes the first air pollutant emission inventory at the national and provincial scale for Lao PDR, covering 2013-2019. Emissions of nine air pollutants, and two greenhouse gases, were quantified using national statistics and international default emission factors. In 2019, national total PM2.5, Nitrogen Oxides (NOx), Black Carbon (BC), Sulphur Dioxide (SO2), Non-Methane Volatile Organic Carbons (NMVOCs), and Ammonia (NH3) were 125, 83, 9.7, 26, 219, and 99 thousand tonnes respectively. Key source sectors include forest fires, residential cooking, agriculture, electricity generation, and transport. However, the contribution of different sources varies across provinces. Forest fires are the primary source determining the spatial trend of particulate air pollution while residential and agricultural emissions contribute more significantly to rural provinces such as Savannakhet. Key sectors in major urban provinces (Vientiane Capital and Xayaboury) are industry, transport and electricity generation. These sectors are also significant sources of greenhouse gases (CO2 and CH4), demonstrating the potential for identification, evaluation and prioritisation of actions that simultaneously improve air quality and achieve Lao PDR’s international climate change commitments

Critical assessment of automated flow cytometry data analysis techniques

Traditional methods for flow cytometry (FCM) data processing rely on subjective manual gating. Recently, several groups have developed computational methods for identifying cell populations in multidimensional FCM data. The Flow Cytometry: Critical Assessment of Population Identification Methods (FlowCAP) challenges were established to compare the performance of these methods on two tasks: (i) mammalian cell population identification, to determine whether automated algorithms can reproduce expert manual gating and (ii) sample classification, to determine whether analysis pipelines can identify characteristics that correlate with external variables (such as clinical outcome). This analysis presents the results of the first FlowCAP challenges. Several methods performed well as compared to manual gating or external variables using statistical performance measures, which suggests that automated methods have reached a sufficient level of maturity and accuracy for reliable use in FCM data analysis.