One of the most serious challenges threatening agricultural sustainability in Nigeria is land degradation. Although this issue has received little attention, soil and water conservation practices have been identified as a possible pathway out of the potential problems posed by land degradation. Therefore, the central research question that this paper tries to address is the following: Do adoption of soil and water conservation (SWC) practices affect crop productivity and household welfare? This paper uses data collected by the International Institute of Tropical Agriculture (IITA) from maize farmers in rural Nigeria. We usedemploy the propensity score matching (PSM), inverse probability weighting adjusted regression model (IPWRA) approach, and the linear regression with endogenous treatment effect (LRETE) model to incorporate the typologies of SWC practices, and tested how the model affects crop productivity and household welfare. Additionally, multinomial logit was used to estimate the factors influencing the decision to adopt single and multiple SWC practices. The estimates show that education, age of the household head, access to credit, experience of drought, soil fertility, and occupational stress contribute to the decision to adopt SWC practices. The casual effect estimates reveal that both single and multiple adoptions of SWC practices had a positive and significant relationship with the crop productivity and welfare of the adopters. The results show that the adoption of combined SWC practices has a higher impact on crop productivity and welfare than single SWC practices. For instance, the adoption of a combination of three SWC practices was found to increase crop productivity and household welfare by 27.55% and 38.23%, respectively versus 13.91% and 15.11% in the case of single SWC practices. The study suggests that profile-raising agenda and efforts that focus on promoting the adoption of combination of SWC practices should be designed and implemented to enhance crop productivity and hence the welfare of the maize farming households in rural Nigeria.

Because people spend most of their time indoors, the characterization of indoor air quality is important for exposure assessment. Unfortunately, indoor air data are scarce, leading to a major data gap in risk assessment. In this study, PM2.5 concentrations in both indoor and outdoor air were simultaneously measured using on-line particulate counters in 13 households in Haidian, Beijing for both heating and non-heating seasons. A bimodal distribution of PM2.5 concentrations suggests rapid transitions between polluted and non-polluted situations. The PM2.5 concentrations in indoor and outdoor air varied synchronously, with the indoor variation lagging. The lag time in the heating season was longer than that in the non-heating season. The particle sizes in indoor air were smaller than those in ambient air in the heating season and vice versa in the non-heating season. PM2.5 concentrations in indoor air were generally lower than those in ambient air except when ambient concentrations dropped sharply to very low levels or there were internal emissions from cooking or other activities. The effectiveness of an air cleaner to reduce indoor PM2.5 concentrations was demonstrated. Non-linear regression models were developed to predict indoor air PM2.5 concentrations based on ambient data with lag time incorporated. The models were applied to estimate the overall population exposure to PM2.5 and the health consequences in Haidian. The health impacts would be significantly overestimated without the indoor exposure being taken into consideration, and this bias would increase as the ambient air quality improved in the future.

Atmospheric PM10 were measured for 12 months at 18 sites along a 2500 km profile across northern China. Annual mean PM10 concentrations in urban, rural village, and rural field sites were 180 ± 171, 182 ± 154, and 128 ± 89 μg/m3, respectively. The similarities in PM10 concentrations between urban and rural village sites suggest that strong localized emissions and severe contamination in rural residential areas are derived from solid fuels combustion in households. High PM10 concentrations in Wuwei and Taiyuan were caused by either sandstorms or industrial activities. Relatively low PM10 concentrations were observed in coastal areas of Dalian and Yantai. Particulate air pollution was much higher in winter and spring than in summer and fall. Multiple regression analysis indicates that 35% of the total variance can be attributed to sandstorms, precipitation and residential energy consumption. Over 40% of the measurements in both urban and rural village areas exceeded the national ambient air quality standard.

To identify different NO₃ ⁻ sources in surface water and to estimate their proportional contribution to the nitrate mixture in surface water, a dual isotope and a Bayesian isotope mixing model have been applied for six different surface waters affected by agriculture, greenhouses in an agricultural area, and households. Annual mean δ¹⁵N–NO₃ ⁻ were between 8.0 and 19.4‰, while annual mean δ¹⁸O–NO₃ ⁻ were given by 4.5–30.7‰. SIAR was used to estimate the proportional contribution of five potential NO₃ ⁻ sources (NO₃ ⁻ in precipitation, NO₃ ⁻ fertilizer, NH₄ ⁺ in fertilizer and rain, soil N, and manure and sewage). SIAR showed that “manure and sewage” contributed highest, “soil N”, “NO₃ ⁻ fertilizer” and “NH₄ ⁺ in fertilizer and rain” contributed middle, and “NO₃ ⁻ in precipitation” contributed least. The SIAR output can be considered as a “fingerprint” for the NO₃ ⁻ source contributions. However, the wide range of isotope values observed in surface water and of the NO₃ ⁻ sources limit its applicability.

Anthropogenic perfluorinated compounds (PFCs), especially the perfluoroalkyl acids (PFAAs) are ubiquitously found in surface waters around the globe. Emissions from households, industries and also atmospheric transport/deposition are discussed as the possible sources. In this study, these sources are evaluated using Switzerland as the study area. Forty-four surface water locations in different rivers and an Alpine lake were investigated for 14 PFAAs, four precursors and acesulfame, an artificial sweetener used as a population marker. Concentrations of individual PFAAs were generally low, between 0.02 and 10 ng/L. Correlation analysis showed that some PFAAs concentrations correlated well with population and less with catchment area, indicating that emissions from population, i.e., from consumer products, is the most important source to surface waters in Switzerland. The correlation with the population marker acesulfame confirmed this observation but highlighted also a few elevated PFAA levels, some of which could be attributed to industrial emissions.

Biomass burning as fuel in the traditional grass-roofed rural households of Western Province of Kenya in open fire places, in poorly ventilated conditions, lead to accumulation of soot under the roofs. This study characterized and quantified the polycyclic aromatic hydrocarbons (PAHs) in accumulated soot in these households and determined the variation in PAHs concentrations with fuel biomass type. Soot samples collected from the households were extracted, cleaned and analysed by gas chromatography. The PAHs were identified using retention times, verified by gas chromatographic mass spectral analysis and quantified from peak area responses using the internal standard method. The PAHs levels significantly varied (P≤0.05) with biomass type in the order: dung≥indigenous trees≥exotic trees≥shrubs and crop residues. Use of dung and wood from indigenous trees as fuel should be discouraged since they are higher emitters (P≤0.05) of carcinogenic PAHs.

In this study, total concentration and inhalation bioaccessibility (dissolution in simulated biological solution) of trace elements (TE) and rare earth elements (REE) were assessed in PM₁₀ from Canadian house dust samples with smoking (n = 25) and non-smoking (n = 25) status. Compared to the natural background concentrations in Canadian soils, median Zn, Pb, Cd and Cu concentrations in PM₁₀ were 10–23 fold higher, while median La, Ce and Pr concentrations were 1.6–2.4 fold higher. Mann-Whitney tests (α = 0.05) indicated no difference between the median TE concentrations based on the smoking status of the household; however, median REE concentrations were significantly higher in the PM₁₀ of smoking households. Additionally, Cd and Ni were positively correlated (Spearman r, p < 0.05) to La, Ce and Nd in smoking households, suggesting that tobacco combustion may have contributed REE in the PM₁₀ of these households. Median inhalation-ingestion bioaccessibility assay outcomes of arsenic (As) and lead (Pb) was higher in the non-smoking households when compared to smoking households (Mann Whitney test, α = 0.05), suggesting that tobacco combustion products may be associated with less soluble species of As and Pb. Although REE bioaccessibility was negligible in simulated lung epithelial fluid regardless of the smoking status of the household, bioaccessibility in the lung-gastric phase was 23.6–27.6% in the smoking household and 34.7–36.7% in the non-smoking households, indicating a significantly lower REE dissolution in PM₁₀ of smoking households. In contrast, between 17 and 21.9% bioaccessibility of REE was observed when artificial lysosomal fluid was used, where the outcome was not significantly affected by the smoking status. This study indicates that despite a higher median REE concentration in the PM₁₀ of smoking households, inhalation bioaccessibility may be significantly influenced by the mineralogy.

Quantitating the health effects of employment history in factories, especially polluting ones, is essential for understanding the benefits or losses of industrialization in rural areas. Using a traced subset of nationwide panel data from 2005 covering five provinces, 101 villages, and 2026 households (collected recently in 2016) and the econometric models, this study estimated the effect of factory employment history on workers' health. The results showed that: the absolute number of factory workers increased from 1998 to 2015, and the proportion of factory workers was 7.68% in 2015; the absolute number and the proportion of farmers decreased from 63.84% in 1998 to 29.06% in 2015. Given that all the respondents live in rural areas, the HlthPlace (the first place the individual went to for their last illness in 2015) was selected as the main dependent variable of interest, and Hlthexp (Healthcare expenditure per person at last illness in 2015) and self-reported health were used as auxiliary dependent variables. The findings revealed that, after controlling the characteristics of individual, household, hospital and area, a one year increase of factory employment history corresponded to a 0.035 level increase in the probability of people choosing high-level hospital (p < 0.01) and a 237.61 yuan increase in healthcare expenditure (p < 0.1). The results also showed the adverse effect of self-reported health on factory employment history (p < 0.01). In addition, the relationship between the farming history and health was evaluated, and the econometric results showed that compared with factory employment history, farming history had opposite impacts on health (p < 0.01). Finally, the robustness check showed that the empirical results were reliable and that the initial results were robust. Generally, this study revealed the effect of overall factory employment on health, which is a useful research supplement to the studies on the health effects of specific pollution exposure.

Cooking and heating with solid fuels results in high levels of household air pollutants, including particulate matter (PM); however, limited data exist for size fractions smaller than PM₂.₅ (diameter less than 2.5 μm). We collected 24-h time-resolved measurements of PM₂.₅ (n = 27) and particle number concentrations (PNC, average diameter 10–700 nm) (n = 44; 24 with paired PM₂.₅ and PNC) in homes with wood-burning traditional and Justa (i.e., with an engineered combustion chamber and chimney) cookstoves in rural Honduras.The median 24-h PM₂.₅ concentration (n = 27) was 79 μg/m³ (interquartile range [IQR]: 44–174 μg/m³); traditional (n = 15): 130 μg/m³ (IQR: 48–250 μg/m³); Justa (n = 12): 66 μg/m³ (IQR: 44–97 μg/m³). The median 24-h PNC (n = 44) was 8.5 × 10⁴ particles (pt)/cm³ (IQR: 3.8 × 10⁴–1.8 × 10⁵ pt/cm³); traditional (n = 27): 1.3 × 10⁵ pt/cm³ (IQR: 3.3 × 10⁴–2.0 × 10⁵ pt/cm³); Justa (n = 17): 6.3 × 10⁴ pt/cm³ (IQR: 4.0 × 10⁴–1.2 × 10⁵ pt/cm³). The 24-h average PM₂.₅ and particle number concentrations were correlated for the full sample of cookstoves (n = 24, Spearman ρ: 0.83); correlations between PM₂.₅ and PNC were higher in traditional stove kitchens (n = 12, ρ: 0.93) than in Justa stove kitchens (n = 12, ρ: 0.67). The 24-h average concentrations of PM₂.₅ and PNC were also correlated with the maximum average concentrations during shorter-term averaging windows of one-, five-, 15-, and 60-min, respectively (Spearman ρ: PM₂.₅ [0.65, 0.85, 0.82, 0.71], PNC [0.74, 0.86, 0.88, 0.86]).Given the moderate correlations observed between 24-h PM₂.₅ and PNC and between 24-h and the shorter-term averaging windows within size fractions, investigators may need to consider cost-effectiveness and information gained by measuring both size fractions for the study objective. Further evaluations of other stove and fuel combinations are needed.